diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..f8b96c635e26681eda18bab06fcf07886c6e720b --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:606c1d714389dff29546575ed2478a85e8edccc28ce1dd0083f2b229b25c329d +size 329869 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..f6ca5b381ef97edabad3ca8ac082495135c3ef3b --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json @@ -0,0 +1,70 @@ +{ + "results": { + "arc_challenge": { + "acc,none": 0.41723549488054607, + "acc_stderr,none": 0.014409825518403075, + "acc_norm,none": 0.4641638225255973, + "acc_norm_stderr,none": 0.01457381366473572, + "alias": "arc_challenge" + } + }, + "configs": { + "arc_challenge": { + "task": "arc_challenge", + "group": [ + "ai2_arc" + ], + "dataset_path": "allenai/ai2_arc", + "dataset_name": "ARC-Challenge", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "Question: {{question}}\nAnswer:", + "doc_to_target": "{{choices.label.index(answerKey)}}", + "doc_to_choice": "{{choices.text}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "Question: {{question}}\nAnswer:", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "arc_challenge": 1.0 + }, + "n-shot": { + "arc_challenge": 1 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..c53e9582805b4b414b8d7c24ac12366e24dd03a0 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6a8f79fe888ab683bc37bec5ecbcb41aa13bd798b6ba25d767aefff388e1606e +size 41958 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..8b767bc21b7bad301bd491404049f49645c9c71c --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3db453642cafc7542d4bade86566d81449fd7992060e54418c3a7789a9d46296 +size 1077245 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..4902008e041be1e3f3b53898917d5574bbaf8cc8 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json @@ -0,0 +1,70 @@ +{ + "results": { + "arc_challenge": { + "acc,none": 0.4300341296928328, + "acc_stderr,none": 0.014467631559138007, + "acc_norm,none": 0.4761092150170648, + "acc_norm_stderr,none": 0.014594701798071655, + "alias": "arc_challenge" + } + }, + "configs": { + "arc_challenge": { + "task": "arc_challenge", + "group": [ + "ai2_arc" + ], + "dataset_path": "allenai/ai2_arc", + "dataset_name": "ARC-Challenge", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "Question: {{question}}\nAnswer:", + "doc_to_target": "{{choices.label.index(answerKey)}}", + "doc_to_choice": "{{choices.text}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 10, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "Question: {{question}}\nAnswer:", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "arc_challenge": 1.0 + }, + "n-shot": { + "arc_challenge": 10 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 16 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..942aa05375d8c186fa60a4d5781e8561113bba9e --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9c43a1e33d929fdd0baef800b09b9c18a2d2a19f84d532f7c067d9e4998fd070 +size 164403 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..378bfc399fa9a866b6247032c5dd3d68a402f555 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:62db1c3c1b7738bdf3ca09f406aa16ddb0da83dcfbd0695b6c00f2b9716ac27d +size 424798 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..63ac22b0c08d97fd32eb8fd24199e3659a2ce805 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json @@ -0,0 +1,70 @@ +{ + "results": { + "arc_challenge": { + "acc,none": 0.42235494880546076, + "acc_stderr,none": 0.014434138713379998, + "acc_norm,none": 0.46245733788395904, + "acc_norm_stderr,none": 0.014570144495075578, + "alias": "arc_challenge" + } + }, + "configs": { + "arc_challenge": { + "task": "arc_challenge", + "group": [ + "ai2_arc" + ], + "dataset_path": "allenai/ai2_arc", + "dataset_name": "ARC-Challenge", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "Question: {{question}}\nAnswer:", + "doc_to_target": "{{choices.label.index(answerKey)}}", + "doc_to_choice": "{{choices.text}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "Question: {{question}}\nAnswer:", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "arc_challenge": 1.0 + }, + "n-shot": { + "arc_challenge": 2 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..c62ea400a763ef7143dead8060d5b37459eff8ae --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fb6044012ea315ee7553f0903739529c1ddc63f02984d420650e15173df2c301 +size 41958 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..e17a48e46fad4a46e20a4b7fee64c638fdd6213e --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0c01cfe4dde9cc86cf2a355d37c31c20b95934f2ce19f1599037d874fc641e9a +size 2212513 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..e2e06ca2fb40d23171d8d00b933e934c148d566b --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json @@ -0,0 +1,70 @@ +{ + "results": { + "arc_challenge": { + "acc,none": 0.4300341296928328, + "acc_stderr,none": 0.014467631559138008, + "acc_norm,none": 0.47696245733788395, + "acc_norm_stderr,none": 0.014595873205358276, + "alias": "arc_challenge" + } + }, + "configs": { + "arc_challenge": { + "task": "arc_challenge", + "group": [ + "ai2_arc" + ], + "dataset_path": "allenai/ai2_arc", + "dataset_name": "ARC-Challenge", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "Question: {{question}}\nAnswer:", + "doc_to_target": "{{choices.label.index(answerKey)}}", + "doc_to_choice": "{{choices.text}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 25, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "Question: {{question}}\nAnswer:", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "arc_challenge": 1.0 + }, + "n-shot": { + "arc_challenge": 25 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 8 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..1485f0b2d1ede4b1596fa445d07bc36638940d5f --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8b3897289f6f8bd3237e395179fb441b74f9f9047ebb63593ad3a7324780b2fe +size 45834 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..94fd2b3fe4212cfd523e25272a8f444265858040 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2e50b7e08b0c04df5a8a82b4b1bc12cd3ff9e19d66fd626baab2ac45fdbfcda1 +size 681746 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..8401d7e653b82084fd0c0ffbfef92cec2559380e --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json @@ -0,0 +1,70 @@ +{ + "results": { + "arc_challenge": { + "acc,none": 0.43600682593856654, + "acc_stderr,none": 0.014491225699230916, + "acc_norm,none": 0.4735494880546075, + "acc_norm_stderr,none": 0.014590931358120167, + "alias": "arc_challenge" + } + }, + "configs": { + "arc_challenge": { + "task": "arc_challenge", + "group": [ + "ai2_arc" + ], + "dataset_path": "allenai/ai2_arc", + "dataset_name": "ARC-Challenge", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "Question: {{question}}\nAnswer:", + "doc_to_target": "{{choices.label.index(answerKey)}}", + "doc_to_choice": "{{choices.text}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "Question: {{question}}\nAnswer:", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "arc_challenge": 1.0 + }, + "n-shot": { + "arc_challenge": 5 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 32 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..45cda51aa574480bd790326f393e4053e2511832 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/arc_challenge/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:11ce3fdaaf87dcb954e58bbdd0e8e4f5dd7992aed05474340731167a4b2e1542 +size 43830 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..bcd52db66a87a252e8f2535f9e010e16a9610910 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3d5a04ea374f31341821a828d13530e06f25c144e91312927a922d17b4c2e748 +size 6656902 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..d3082a16bd9f0b8f8f56f6cb8cd6586cf5b2772e --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json @@ -0,0 +1,68 @@ +{ + "results": { + "hellaswag": { + "acc,none": 0.5177255526787492, + "acc_stderr,none": 0.004986644894743122, + "acc_norm,none": 0.6976697868950408, + "acc_norm_stderr,none": 0.004583289072937751, + "alias": "hellaswag" + } + }, + "configs": { + "hellaswag": { + "task": "hellaswag", + "group": [ + "multiple_choice" + ], + "dataset_path": "hellaswag", + "training_split": "train", + "validation_split": "validation", + "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n def _process_doc(doc):\n ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n out_doc = {\n \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n \"gold\": int(doc[\"label\"]),\n }\n return out_doc\n\n return dataset.map(_process_doc)\n", + "doc_to_text": "{{query}}", + "doc_to_target": "{{label}}", + "doc_to_choice": "choices", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "hellaswag": 1.0 + }, + "n-shot": { + "hellaswag": 1 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..2fe206585f2c467b206b21176ab69ce247512143 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7030ed476b156a711aac97c6b769f351444f337d34649739bf5d2b8a0d0c36d1 +size 51632 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..e18c93858f56fd1072c79c92d8b4197f7d9a6d1a --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e9d837b45c58dc0ff298525707c58ed81b08c7eeb93682322a1895cd192ce88e +size 20818899 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..c6b83244328bbee973ca66231b3afe9ebb48b042 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json @@ -0,0 +1,68 @@ +{ + "results": { + "hellaswag": { + "acc,none": 0.5270862378012349, + "acc_stderr,none": 0.004982454383162069, + "acc_norm,none": 0.7167894841665007, + "acc_norm_stderr,none": 0.004496369742132106, + "alias": "hellaswag" + } + }, + "configs": { + "hellaswag": { + "task": "hellaswag", + "group": [ + "multiple_choice" + ], + "dataset_path": "hellaswag", + "training_split": "train", + "validation_split": "validation", + "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n def _process_doc(doc):\n ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n out_doc = {\n \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n \"gold\": int(doc[\"label\"]),\n }\n return out_doc\n\n return dataset.map(_process_doc)\n", + "doc_to_text": "{{query}}", + "doc_to_target": "{{label}}", + "doc_to_choice": "choices", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 10, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "hellaswag": 1.0 + }, + "n-shot": { + "hellaswag": 10 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 8 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..29aada7ab3bc26b109e4f7600cb453fa2e230316 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b71e0b17189ed9af3a3304c0202efec2f8461961fd58e6f37b60051995207127 +size 84683 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..de696e63092c5f365701b8c57082779f50dcccf8 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3a2d96a347c42118a571089112f72f8f42ab297ea4bac567972bda2d4102f1c9 +size 8347910 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..5da648059d1055b812378a7286b339b720c1e110 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json @@ -0,0 +1,68 @@ +{ + "results": { + "hellaswag": { + "acc,none": 0.5218084047002589, + "acc_stderr,none": 0.004985032806802434, + "acc_norm,none": 0.702051384186417, + "acc_norm_stderr,none": 0.004564220870531572, + "alias": "hellaswag" + } + }, + "configs": { + "hellaswag": { + "task": "hellaswag", + "group": [ + "multiple_choice" + ], + "dataset_path": "hellaswag", + "training_split": "train", + "validation_split": "validation", + "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n def _process_doc(doc):\n ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n out_doc = {\n \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n \"gold\": int(doc[\"label\"]),\n }\n return out_doc\n\n return dataset.map(_process_doc)\n", + "doc_to_text": "{{query}}", + "doc_to_target": "{{label}}", + "doc_to_choice": "choices", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "hellaswag": 1.0 + }, + "n-shot": { + "hellaswag": 2 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..129837829b6cafa4cd8da908438b6eefddee04d2 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:94c0529d0c355e7549cd2660abcbce9912544cdca62d903109c86c48476cd51b +size 50306 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..d702bfaeff54b1a4d45f9f76f1ab72c5b3dcc191 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dc2638855acf1b3cedd27cce2e8522451eb180a819c4c5eb1af64c473507e5c3 +size 45106723 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..087a9a983ced1bdca80d9e60299668a5b23504d8 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json @@ -0,0 +1,68 @@ +{ + "results": { + "hellaswag": { + "acc,none": 0.530870344552878, + "acc_stderr,none": 0.004980262025472473, + "acc_norm,none": 0.7227643895638319, + "acc_norm_stderr,none": 0.004467189716140494, + "alias": "hellaswag" + } + }, + "configs": { + "hellaswag": { + "task": "hellaswag", + "group": [ + "multiple_choice" + ], + "dataset_path": "hellaswag", + "training_split": "train", + "validation_split": "validation", + "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n def _process_doc(doc):\n ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n out_doc = {\n \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n \"gold\": int(doc[\"label\"]),\n }\n return out_doc\n\n return dataset.map(_process_doc)\n", + "doc_to_text": "{{query}}", + "doc_to_target": "{{label}}", + "doc_to_choice": "choices", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 25, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "hellaswag": 1.0 + }, + "n-shot": { + "hellaswag": 25 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 8 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..7c9e2a758ced6a423a8e42b6fb13aa76d82abca9 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7cdf1173cdb56c1a06000a7d76b15eab6d8468be5d31cddedd13b7aa8962b985 +size 87299 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..f72114636cfbdaf7753e4528adc775d36f7135e2 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:663e3c42edb505346df7276a18854babb8fb789400c212f227d1fb3693a0c74f +size 13182828 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..8468bbffbd36a191dddeae44baafc50c40bb55ac --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json @@ -0,0 +1,68 @@ +{ + "results": { + "hellaswag": { + "acc,none": 0.527185819557857, + "acc_stderr,none": 0.004982400368939668, + "acc_norm,none": 0.7122087233618801, + "acc_norm_stderr,none": 0.004518080594528022, + "alias": "hellaswag" + } + }, + "configs": { + "hellaswag": { + "task": "hellaswag", + "group": [ + "multiple_choice" + ], + "dataset_path": "hellaswag", + "training_split": "train", + "validation_split": "validation", + "process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n def _process_doc(doc):\n ctx = doc[\"ctx_a\"] + \" \" + doc[\"ctx_b\"].capitalize()\n out_doc = {\n \"query\": preprocess(doc[\"activity_label\"] + \": \" + ctx),\n \"choices\": [preprocess(ending) for ending in doc[\"endings\"]],\n \"gold\": int(doc[\"label\"]),\n }\n return out_doc\n\n return dataset.map(_process_doc)\n", + "doc_to_text": "{{query}}", + "doc_to_target": "{{label}}", + "doc_to_choice": "choices", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + }, + { + "metric": "acc_norm", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "hellaswag": 1.0 + }, + "n-shot": { + "hellaswag": 5 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 32 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..87553bb110cb7b122c31a0c70e1aef9ca7d2b5a2 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/hellaswag/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a92e99965167f778329e92ba5056828fc4ebc0d12daef47a3cdc357faee509b7 +size 55177 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..1afb894cde3ecade490e796446a3bef47ebacfbd --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:faa8c04050b605cf1c8f2e5dd9cca1ecdd96690354a293ba67f2705c7e50c4db +size 5218162 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..241a1e1fb82c9b36e7badadefe9cea4163c1c46f --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,252 @@ +{ + "results": { + "lambada_multilingual": { + "perplexity,none": 21.000049955979808, + "perplexity_stderr,none": 6.40017218612115, + "acc,none": 0.537356879487677, + "acc_stderr,none": 0.06283288884259476, + "alias": "lambada_multilingual" + }, + "lambada_openai_mt_de": { + "perplexity,none": 34.40995706565969, + "perplexity_stderr,none": 1.9198882405259308, + "acc,none": 0.42751795070832527, + "acc_stderr,none": 0.0068923954478686475, + "alias": " - lambada_openai_mt_de" + }, + "lambada_openai_mt_en": { + "perplexity,none": 3.376233478695252, + "perplexity_stderr,none": 0.0662417387622138, + "acc,none": 0.7432563555210557, + "acc_stderr,none": 0.006085990070284605, + "alias": " - lambada_openai_mt_en" + }, + "lambada_openai_mt_es": { + "perplexity,none": 29.08178023365845, + "perplexity_stderr,none": 1.438828440779044, + "acc,none": 0.4486706772753736, + "acc_stderr,none": 0.006929173919665489, + "alias": " - lambada_openai_mt_es" + }, + "lambada_openai_mt_fr": { + "perplexity,none": 16.477136806072853, + "perplexity_stderr,none": 0.8029953639024064, + "acc,none": 0.5476421502037648, + "acc_stderr,none": 0.006934283157219039, + "alias": " - lambada_openai_mt_fr" + }, + "lambada_openai_mt_it": { + "perplexity,none": 21.65514219581279, + "perplexity_stderr,none": 1.1521232467165174, + "acc,none": 0.5196972637298661, + "acc_stderr,none": 0.006960570207731863, + "alias": " - lambada_openai_mt_it" + } + }, + "groups": { + "lambada_multilingual": { + "perplexity,none": 21.000049955979808, + "perplexity_stderr,none": 6.40017218612115, + "acc,none": 0.537356879487677, + "acc_stderr,none": 0.06283288884259476, + "alias": "lambada_multilingual" + } + }, + "configs": { + "lambada_openai_mt_de": { + "task": "lambada_openai_mt_de", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "de", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_en": { + "task": "lambada_openai_mt_en", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "en", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_es": { + "task": "lambada_openai_mt_es", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "es", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_fr": { + "task": "lambada_openai_mt_fr", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "fr", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_it": { + "task": "lambada_openai_mt_it", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "it", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "lambada_multilingual": "N/A", + "lambada_openai_mt_de": 1.0, + "lambada_openai_mt_en": 1.0, + "lambada_openai_mt_es": 1.0, + "lambada_openai_mt_fr": 1.0, + "lambada_openai_mt_it": 1.0 + }, + "n-shot": { + "lambada_multilingual": 0, + "lambada_openai_mt_de": 0, + "lambada_openai_mt_en": 0, + "lambada_openai_mt_es": 0, + "lambada_openai_mt_fr": 0, + "lambada_openai_mt_it": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..18f5c99d7a2e95f038d50ca1dec6b0ee396d8afd --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c76f26a7d4c6549f6f9e03a6eaeab506018ec6e3fd1160a19751764d733a3c06 +size 67853 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..d58586faf39c099ab83c7b0a2f7f0dd5ffbcc524 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a59db7139a5f7b727b6c6bb0cec13f1627fb33f4abf9a29bdf9a228b5e436158 +size 5218026 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..f508d987bcec6a0c152132b8e1b584b0da22c374 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,252 @@ +{ + "results": { + "lambada_multilingual": { + "perplexity,none": 20.99725893141735, + "perplexity_stderr,none": 8.213261901364534, + "acc,none": 0.5373180671453522, + "acc_stderr,none": 0.084854928421691, + "alias": "lambada_multilingual" + }, + "lambada_openai_mt_de": { + "perplexity,none": 34.40417838764442, + "perplexity_stderr,none": 1.9194150131315955, + "acc,none": 0.42732388899670093, + "acc_stderr,none": 0.00689199878844782, + "alias": " - lambada_openai_mt_de" + }, + "lambada_openai_mt_en": { + "perplexity,none": 3.3752600927697225, + "perplexity_stderr,none": 0.06620127895333149, + "acc,none": 0.7432563555210557, + "acc_stderr,none": 0.006085990070284606, + "alias": " - lambada_openai_mt_en" + }, + "lambada_openai_mt_es": { + "perplexity,none": 29.07358750583119, + "perplexity_stderr,none": 1.4383741470995577, + "acc,none": 0.44905880069862214, + "acc_stderr,none": 0.006929729843881883, + "alias": " - lambada_openai_mt_es" + }, + "lambada_openai_mt_fr": { + "perplexity,none": 16.47843119038625, + "perplexity_stderr,none": 0.8030140849186048, + "acc,none": 0.5476421502037648, + "acc_stderr,none": 0.006934283157219039, + "alias": " - lambada_openai_mt_fr" + }, + "lambada_openai_mt_it": { + "perplexity,none": 21.65483748045518, + "perplexity_stderr,none": 1.152131238974256, + "acc,none": 0.5193091403066175, + "acc_stderr,none": 0.0069607812884263836, + "alias": " - lambada_openai_mt_it" + } + }, + "groups": { + "lambada_multilingual": { + "perplexity,none": 20.99725893141735, + "perplexity_stderr,none": 8.213261901364534, + "acc,none": 0.5373180671453522, + "acc_stderr,none": 0.084854928421691, + "alias": "lambada_multilingual" + } + }, + "configs": { + "lambada_openai_mt_de": { + "task": "lambada_openai_mt_de", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "de", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_en": { + "task": "lambada_openai_mt_en", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "en", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_es": { + "task": "lambada_openai_mt_es", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "es", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_fr": { + "task": "lambada_openai_mt_fr", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "fr", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + }, + "lambada_openai_mt_it": { + "task": "lambada_openai_mt_it", + "group": [ + "lambada_multilingual" + ], + "dataset_path": "EleutherAI/lambada_openai", + "dataset_name": "it", + "test_split": "test", + "doc_to_text": "{{text.split(' ')[:-1]|join(' ')}}", + "doc_to_target": "{{' '+text.split(' ')[-1]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "perplexity", + "aggregation": "perplexity", + "higher_is_better": false + }, + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "loglikelihood", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{text}}", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "lambada_multilingual": "N/A", + "lambada_openai_mt_de": 1.0, + "lambada_openai_mt_en": 1.0, + "lambada_openai_mt_es": 1.0, + "lambada_openai_mt_fr": 1.0, + "lambada_openai_mt_it": 1.0 + }, + "n-shot": { + "lambada_multilingual": 0, + "lambada_openai_mt_de": 0, + "lambada_openai_mt_en": 0, + "lambada_openai_mt_es": 0, + "lambada_openai_mt_fr": 0, + "lambada_openai_mt_it": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "c8d9bbd" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..ad3caa284757cff0550be01eea67f10cd9ff33d0 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/lambada_multilingual/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:420be7924a2cc3a7d1ebfa9c1d9aff971ec4cb50379d0508aeed12d7ce8aa508 +size 68224 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..aa7d67370d73bcd68b93ffc03723f32fc657e3fc --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9f6a6693e11c5dfb17ee390db1a90ab57e078db75fbef6af2e90e7fc0becb58e +size 4234089 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..c70cf6be87ed9e86ab5c319f7672a626a70c42d5 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json @@ -0,0 +1,2651 @@ +{ + "results": { + "mmlu": { + "acc,none": 0.3064378293690358, + "acc_stderr,none": 0.04981928640245539, + "alias": "mmlu" + }, + "mmlu_humanities": { + "alias": " - humanities", + "acc,none": 0.2913921360255048, + "acc_stderr,none": 0.04490801351337553 + }, + "mmlu_formal_logic": { + "alias": " - formal_logic", + "acc,none": 0.29365079365079366, + "acc_stderr,none": 0.040735243221471255 + }, + "mmlu_high_school_european_history": { + "alias": " - high_school_european_history", + "acc,none": 0.4121212121212121, + "acc_stderr,none": 0.03843566993588717 + }, + "mmlu_high_school_us_history": { + "alias": " - high_school_us_history", + "acc,none": 0.35294117647058826, + "acc_stderr,none": 0.03354092437591519 + }, + "mmlu_high_school_world_history": { + "alias": " - high_school_world_history", + "acc,none": 0.3291139240506329, + "acc_stderr,none": 0.03058732629470236 + }, + "mmlu_international_law": { + "alias": " - international_law", + "acc,none": 0.2396694214876033, + "acc_stderr,none": 0.03896878985070417 + }, + "mmlu_jurisprudence": { + "alias": " - jurisprudence", + "acc,none": 0.28703703703703703, + "acc_stderr,none": 0.043733130409147614 + }, + "mmlu_logical_fallacies": { + "alias": " - logical_fallacies", + "acc,none": 0.26993865030674846, + "acc_stderr,none": 0.03487825168497892 + }, + "mmlu_moral_disputes": { + "alias": " - moral_disputes", + "acc,none": 0.3265895953757225, + "acc_stderr,none": 0.025248264774242826 + }, + "mmlu_moral_scenarios": { + "alias": " - moral_scenarios", + "acc,none": 0.23798882681564246, + "acc_stderr,none": 0.014242630070574885 + }, + "mmlu_philosophy": { + "alias": " - philosophy", + "acc,none": 0.26688102893890675, + "acc_stderr,none": 0.025122637608816646 + }, + "mmlu_prehistory": { + "alias": " - prehistory", + "acc,none": 0.37037037037037035, + "acc_stderr,none": 0.02686949074481525 + }, + "mmlu_professional_law": { + "alias": " - professional_law", + "acc,none": 0.27640156453715775, + "acc_stderr,none": 0.011422153194553576 + }, + "mmlu_world_religions": { + "alias": " - world_religions", + "acc,none": 0.34502923976608185, + "acc_stderr,none": 0.03645981377388806 + }, + "mmlu_other": { + "alias": " - other", + "acc,none": 0.31992275506919854, + "acc_stderr,none": 0.038871837655311235 + }, + "mmlu_business_ethics": { + "alias": " - business_ethics", + "acc,none": 0.22, + "acc_stderr,none": 0.041633319989322716 + }, + "mmlu_clinical_knowledge": { + "alias": " - clinical_knowledge", + "acc,none": 0.33584905660377357, + "acc_stderr,none": 0.02906722014664483 + }, + "mmlu_college_medicine": { + "alias": " - college_medicine", + "acc,none": 0.2947976878612717, + "acc_stderr,none": 0.03476599607516478 + }, + "mmlu_global_facts": { + "alias": " - global_facts", + "acc,none": 0.3, + "acc_stderr,none": 0.046056618647183814 + }, + "mmlu_human_aging": { + "alias": " - human_aging", + "acc,none": 0.3273542600896861, + "acc_stderr,none": 0.03149384670994131 + }, + "mmlu_management": { + "alias": " - management", + "acc,none": 0.32038834951456313, + "acc_stderr,none": 0.0462028408228004 + }, + "mmlu_marketing": { + "alias": " - marketing", + "acc,none": 0.3418803418803419, + "acc_stderr,none": 0.03107502852650775 + }, + "mmlu_medical_genetics": { + "alias": " - medical_genetics", + "acc,none": 0.32, + "acc_stderr,none": 0.046882617226215034 + }, + "mmlu_miscellaneous": { + "alias": " - miscellaneous", + "acc,none": 0.34099616858237547, + "acc_stderr,none": 0.01695178138322331 + }, + "mmlu_nutrition": { + "alias": " - nutrition", + "acc,none": 0.34967320261437906, + "acc_stderr,none": 0.0273053080762747 + }, + "mmlu_professional_accounting": { + "alias": " - professional_accounting", + "acc,none": 0.24822695035460993, + "acc_stderr,none": 0.025770015644290396 + }, + "mmlu_professional_medicine": { + "alias": " - professional_medicine", + "acc,none": 0.3088235294117647, + "acc_stderr,none": 0.02806499816704009 + }, + "mmlu_virology": { + "alias": " - virology", + "acc,none": 0.3373493975903614, + "acc_stderr,none": 0.0368078369072758 + }, + "mmlu_social_sciences": { + "alias": " - social_sciences", + "acc,none": 0.3340916477088073, + "acc_stderr,none": 0.05303756240020363 + }, + "mmlu_econometrics": { + "alias": " - econometrics", + "acc,none": 0.2807017543859649, + "acc_stderr,none": 0.042270544512322 + }, + "mmlu_high_school_geography": { + "alias": " - high_school_geography", + "acc,none": 0.37373737373737376, + "acc_stderr,none": 0.034468977386593325 + }, + "mmlu_high_school_government_and_politics": { + "alias": " - high_school_government_and_politics", + "acc,none": 0.38860103626943004, + "acc_stderr,none": 0.035177397963731316 + }, + "mmlu_high_school_macroeconomics": { + "alias": " - high_school_macroeconomics", + "acc,none": 0.3487179487179487, + "acc_stderr,none": 0.02416278028401772 + }, + "mmlu_high_school_microeconomics": { + "alias": " - high_school_microeconomics", + "acc,none": 0.3067226890756303, + "acc_stderr,none": 0.029953823891887048 + }, + "mmlu_high_school_psychology": { + "alias": " - high_school_psychology", + "acc,none": 0.27155963302752295, + "acc_stderr,none": 0.019069098363191428 + }, + "mmlu_human_sexuality": { + "alias": " - human_sexuality", + "acc,none": 0.35877862595419846, + "acc_stderr,none": 0.04206739313864908 + }, + "mmlu_professional_psychology": { + "alias": " - professional_psychology", + "acc,none": 0.2875816993464052, + "acc_stderr,none": 0.018311653053648222 + }, + "mmlu_public_relations": { + "alias": " - public_relations", + "acc,none": 0.39090909090909093, + "acc_stderr,none": 0.04673752333670237 + }, + "mmlu_security_studies": { + "alias": " - security_studies", + "acc,none": 0.4163265306122449, + "acc_stderr,none": 0.031557828165561644 + }, + "mmlu_sociology": { + "alias": " - sociology", + "acc,none": 0.39303482587064675, + "acc_stderr,none": 0.0345368246603156 + }, + "mmlu_us_foreign_policy": { + "alias": " - us_foreign_policy", + "acc,none": 0.43, + "acc_stderr,none": 0.049756985195624284 + }, + "mmlu_stem": { + "alias": " - stem", + "acc,none": 0.28861401839517925, + "acc_stderr,none": 0.055890566512636665 + }, + "mmlu_abstract_algebra": { + "alias": " - abstract_algebra", + "acc,none": 0.19, + "acc_stderr,none": 0.03942772444036622 + }, + "mmlu_anatomy": { + "alias": " - anatomy", + "acc,none": 0.3037037037037037, + "acc_stderr,none": 0.03972552884785136 + }, + "mmlu_astronomy": { + "alias": " - astronomy", + "acc,none": 0.3355263157894737, + "acc_stderr,none": 0.038424985593952694 + }, + "mmlu_college_biology": { + "alias": " - college_biology", + "acc,none": 0.3402777777777778, + "acc_stderr,none": 0.03962135573486219 + }, + "mmlu_college_chemistry": { + "alias": " - college_chemistry", + "acc,none": 0.36, + "acc_stderr,none": 0.048241815132442176 + }, + "mmlu_college_computer_science": { + "alias": " - college_computer_science", + "acc,none": 0.3, + "acc_stderr,none": 0.046056618647183814 + }, + "mmlu_college_mathematics": { + "alias": " - college_mathematics", + "acc,none": 0.3, + "acc_stderr,none": 0.046056618647183814 + }, + "mmlu_college_physics": { + "alias": " - college_physics", + "acc,none": 0.23529411764705882, + "acc_stderr,none": 0.04220773659171452 + }, + "mmlu_computer_security": { + "alias": " - computer_security", + "acc,none": 0.28, + "acc_stderr,none": 0.045126085985421276 + }, + "mmlu_conceptual_physics": { + "alias": " - conceptual_physics", + "acc,none": 0.35319148936170214, + "acc_stderr,none": 0.031245325202761926 + }, + "mmlu_electrical_engineering": { + "alias": " - electrical_engineering", + "acc,none": 0.3586206896551724, + "acc_stderr,none": 0.03996629574876719 + }, + "mmlu_elementary_mathematics": { + "alias": " - elementary_mathematics", + "acc,none": 0.26455026455026454, + "acc_stderr,none": 0.022717467897708593 + }, + "mmlu_high_school_biology": { + "alias": " - high_school_biology", + "acc,none": 0.3419354838709677, + "acc_stderr,none": 0.026985289576552735 + }, + "mmlu_high_school_chemistry": { + "alias": " - high_school_chemistry", + "acc,none": 0.22660098522167488, + "acc_stderr,none": 0.02945486383529297 + }, + "mmlu_high_school_computer_science": { + "alias": " - high_school_computer_science", + "acc,none": 0.23, + "acc_stderr,none": 0.04229525846816508 + }, + "mmlu_high_school_mathematics": { + "alias": " - high_school_mathematics", + "acc,none": 0.24444444444444444, + "acc_stderr,none": 0.026202766534652148 + }, + "mmlu_high_school_physics": { + "alias": " - high_school_physics", + "acc,none": 0.24503311258278146, + "acc_stderr,none": 0.035118075718047245 + }, + "mmlu_high_school_statistics": { + "alias": " - high_school_statistics", + "acc,none": 0.24537037037037038, + "acc_stderr,none": 0.02934666509437294 + }, + "mmlu_machine_learning": { + "alias": " - machine_learning", + "acc,none": 0.32142857142857145, + "acc_stderr,none": 0.04432804055291519 + } + }, + "groups": { + "mmlu": { + "acc,none": 0.3064378293690358, + "acc_stderr,none": 0.04981928640245539, + "alias": "mmlu" + }, + "mmlu_humanities": { + "alias": " - humanities", + "acc,none": 0.2913921360255048, + "acc_stderr,none": 0.04490801351337553 + }, + "mmlu_other": { + "alias": " - other", + "acc,none": 0.31992275506919854, + "acc_stderr,none": 0.038871837655311235 + }, + "mmlu_social_sciences": { + "alias": " - social_sciences", + "acc,none": 0.3340916477088073, + "acc_stderr,none": 0.05303756240020363 + }, + "mmlu_stem": { + "alias": " - stem", + "acc,none": 0.28861401839517925, + "acc_stderr,none": 0.055890566512636665 + } + }, + "configs": { + "mmlu_abstract_algebra": { + "task": "mmlu_abstract_algebra", + "task_alias": "abstract_algebra", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "abstract_algebra", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_anatomy": { + "task": "mmlu_anatomy", + "task_alias": "anatomy", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "anatomy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about anatomy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_astronomy": { + "task": "mmlu_astronomy", + "task_alias": "astronomy", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "astronomy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about astronomy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_business_ethics": { + "task": "mmlu_business_ethics", + "task_alias": "business_ethics", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "business_ethics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about business ethics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_clinical_knowledge": { + "task": "mmlu_clinical_knowledge", + "task_alias": "clinical_knowledge", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "clinical_knowledge", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_biology": { + "task": "mmlu_college_biology", + "task_alias": "college_biology", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_biology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college biology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_chemistry": { + "task": "mmlu_college_chemistry", + "task_alias": "college_chemistry", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_chemistry", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_computer_science": { + "task": "mmlu_college_computer_science", + "task_alias": "college_computer_science", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_computer_science", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college computer science.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_mathematics": { + "task": "mmlu_college_mathematics", + "task_alias": "college_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_medicine": { + "task": "mmlu_college_medicine", + "task_alias": "college_medicine", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_medicine", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college medicine.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_physics": { + "task": "mmlu_college_physics", + "task_alias": "college_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_computer_security": { + "task": "mmlu_computer_security", + "task_alias": "computer_security", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "computer_security", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about computer security.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_conceptual_physics": { + "task": "mmlu_conceptual_physics", + "task_alias": "conceptual_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "conceptual_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_econometrics": { + "task": "mmlu_econometrics", + "task_alias": "econometrics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "econometrics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about econometrics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_electrical_engineering": { + "task": "mmlu_electrical_engineering", + "task_alias": "electrical_engineering", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "electrical_engineering", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_elementary_mathematics": { + "task": "mmlu_elementary_mathematics", + "task_alias": "elementary_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "elementary_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_formal_logic": { + "task": "mmlu_formal_logic", + "task_alias": "formal_logic", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "formal_logic", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about formal logic.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_global_facts": { + "task": "mmlu_global_facts", + "task_alias": "global_facts", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "global_facts", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about global facts.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_biology": { + "task": "mmlu_high_school_biology", + "task_alias": "high_school_biology", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_biology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school biology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_chemistry": { + "task": "mmlu_high_school_chemistry", + "task_alias": "high_school_chemistry", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_chemistry", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_computer_science": { + "task": "mmlu_high_school_computer_science", + "task_alias": "high_school_computer_science", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_computer_science", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_european_history": { + "task": "mmlu_high_school_european_history", + "task_alias": "high_school_european_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_european_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school european history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_geography": { + "task": "mmlu_high_school_geography", + "task_alias": "high_school_geography", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_geography", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school geography.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_government_and_politics": { + "task": "mmlu_high_school_government_and_politics", + "task_alias": "high_school_government_and_politics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_government_and_politics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_macroeconomics": { + "task": "mmlu_high_school_macroeconomics", + "task_alias": "high_school_macroeconomics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_macroeconomics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_mathematics": { + "task": "mmlu_high_school_mathematics", + "task_alias": "high_school_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_microeconomics": { + "task": "mmlu_high_school_microeconomics", + "task_alias": "high_school_microeconomics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_microeconomics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_physics": { + "task": "mmlu_high_school_physics", + "task_alias": "high_school_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_psychology": { + "task": "mmlu_high_school_psychology", + "task_alias": "high_school_psychology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_psychology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_statistics": { + "task": "mmlu_high_school_statistics", + "task_alias": "high_school_statistics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_statistics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_us_history": { + "task": "mmlu_high_school_us_history", + "task_alias": "high_school_us_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_us_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school us history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_world_history": { + "task": "mmlu_high_school_world_history", + "task_alias": "high_school_world_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_world_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school world history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_human_aging": { + "task": "mmlu_human_aging", + "task_alias": "human_aging", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "human_aging", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about human aging.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_human_sexuality": { + "task": "mmlu_human_sexuality", + "task_alias": "human_sexuality", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "human_sexuality", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_international_law": { + "task": "mmlu_international_law", + "task_alias": "international_law", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "international_law", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about international law.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_jurisprudence": { + "task": "mmlu_jurisprudence", + "task_alias": "jurisprudence", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "jurisprudence", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_logical_fallacies": { + "task": "mmlu_logical_fallacies", + "task_alias": "logical_fallacies", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "logical_fallacies", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_machine_learning": { + "task": "mmlu_machine_learning", + "task_alias": "machine_learning", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "machine_learning", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about machine learning.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_management": { + "task": "mmlu_management", + "task_alias": "management", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "management", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about management.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_marketing": { + "task": "mmlu_marketing", + "task_alias": "marketing", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "marketing", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about marketing.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_medical_genetics": { + "task": "mmlu_medical_genetics", + "task_alias": "medical_genetics", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "medical_genetics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_miscellaneous": { + "task": "mmlu_miscellaneous", + "task_alias": "miscellaneous", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "miscellaneous", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_moral_disputes": { + "task": "mmlu_moral_disputes", + "task_alias": "moral_disputes", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "moral_disputes", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_moral_scenarios": { + "task": "mmlu_moral_scenarios", + "task_alias": "moral_scenarios", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "moral_scenarios", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_nutrition": { + "task": "mmlu_nutrition", + "task_alias": "nutrition", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "nutrition", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about nutrition.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_philosophy": { + "task": "mmlu_philosophy", + "task_alias": "philosophy", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "philosophy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about philosophy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_prehistory": { + "task": "mmlu_prehistory", + "task_alias": "prehistory", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "prehistory", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about prehistory.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_accounting": { + "task": "mmlu_professional_accounting", + "task_alias": "professional_accounting", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_accounting", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_law": { + "task": "mmlu_professional_law", + "task_alias": "professional_law", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_law", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional law.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_medicine": { + "task": "mmlu_professional_medicine", + "task_alias": "professional_medicine", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_medicine", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_psychology": { + "task": "mmlu_professional_psychology", + "task_alias": "professional_psychology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_psychology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_public_relations": { + "task": "mmlu_public_relations", + "task_alias": "public_relations", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "public_relations", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about public relations.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_security_studies": { + "task": "mmlu_security_studies", + "task_alias": "security_studies", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "security_studies", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about security studies.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_sociology": { + "task": "mmlu_sociology", + "task_alias": "sociology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "sociology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about sociology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_us_foreign_policy": { + "task": "mmlu_us_foreign_policy", + "task_alias": "us_foreign_policy", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "us_foreign_policy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_virology": { + "task": "mmlu_virology", + "task_alias": "virology", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "virology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about virology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_world_religions": { + "task": "mmlu_world_religions", + "task_alias": "world_religions", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "world_religions", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about world religions.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + } + }, + "versions": { + "mmlu": "N/A", + "mmlu_abstract_algebra": 0.0, + "mmlu_anatomy": 0.0, + "mmlu_astronomy": 0.0, + "mmlu_business_ethics": 0.0, + "mmlu_clinical_knowledge": 0.0, + "mmlu_college_biology": 0.0, + "mmlu_college_chemistry": 0.0, + "mmlu_college_computer_science": 0.0, + "mmlu_college_mathematics": 0.0, + "mmlu_college_medicine": 0.0, + "mmlu_college_physics": 0.0, + "mmlu_computer_security": 0.0, + "mmlu_conceptual_physics": 0.0, + "mmlu_econometrics": 0.0, + "mmlu_electrical_engineering": 0.0, + "mmlu_elementary_mathematics": 0.0, + "mmlu_formal_logic": 0.0, + "mmlu_global_facts": 0.0, + "mmlu_high_school_biology": 0.0, + "mmlu_high_school_chemistry": 0.0, + "mmlu_high_school_computer_science": 0.0, + "mmlu_high_school_european_history": 0.0, + "mmlu_high_school_geography": 0.0, + "mmlu_high_school_government_and_politics": 0.0, + "mmlu_high_school_macroeconomics": 0.0, + "mmlu_high_school_mathematics": 0.0, + "mmlu_high_school_microeconomics": 0.0, + "mmlu_high_school_physics": 0.0, + "mmlu_high_school_psychology": 0.0, + "mmlu_high_school_statistics": 0.0, + "mmlu_high_school_us_history": 0.0, + "mmlu_high_school_world_history": 0.0, + "mmlu_human_aging": 0.0, + "mmlu_human_sexuality": 0.0, + "mmlu_humanities": "N/A", + "mmlu_international_law": 0.0, + "mmlu_jurisprudence": 0.0, + "mmlu_logical_fallacies": 0.0, + "mmlu_machine_learning": 0.0, + "mmlu_management": 0.0, + "mmlu_marketing": 0.0, + "mmlu_medical_genetics": 0.0, + "mmlu_miscellaneous": 0.0, + "mmlu_moral_disputes": 0.0, + "mmlu_moral_scenarios": 0.0, + "mmlu_nutrition": 0.0, + "mmlu_other": "N/A", + "mmlu_philosophy": 0.0, + "mmlu_prehistory": 0.0, + "mmlu_professional_accounting": 0.0, + "mmlu_professional_law": 0.0, + "mmlu_professional_medicine": 0.0, + "mmlu_professional_psychology": 0.0, + "mmlu_public_relations": 0.0, + "mmlu_security_studies": 0.0, + "mmlu_social_sciences": "N/A", + "mmlu_sociology": 0.0, + "mmlu_stem": "N/A", + "mmlu_us_foreign_policy": 0.0, + "mmlu_virology": 0.0, + "mmlu_world_religions": 0.0 + }, + "n-shot": { + "mmlu": 0, + "mmlu_abstract_algebra": 1, + "mmlu_anatomy": 1, + "mmlu_astronomy": 1, + "mmlu_business_ethics": 1, + "mmlu_clinical_knowledge": 1, + "mmlu_college_biology": 1, + "mmlu_college_chemistry": 1, + "mmlu_college_computer_science": 1, + "mmlu_college_mathematics": 1, + "mmlu_college_medicine": 1, + "mmlu_college_physics": 1, + "mmlu_computer_security": 1, + "mmlu_conceptual_physics": 1, + "mmlu_econometrics": 1, + "mmlu_electrical_engineering": 1, + "mmlu_elementary_mathematics": 1, + "mmlu_formal_logic": 1, + "mmlu_global_facts": 1, + "mmlu_high_school_biology": 1, + "mmlu_high_school_chemistry": 1, + "mmlu_high_school_computer_science": 1, + "mmlu_high_school_european_history": 1, + "mmlu_high_school_geography": 1, + "mmlu_high_school_government_and_politics": 1, + "mmlu_high_school_macroeconomics": 1, + "mmlu_high_school_mathematics": 1, + "mmlu_high_school_microeconomics": 1, + "mmlu_high_school_physics": 1, + "mmlu_high_school_psychology": 1, + "mmlu_high_school_statistics": 1, + "mmlu_high_school_us_history": 1, + "mmlu_high_school_world_history": 1, + "mmlu_human_aging": 1, + "mmlu_human_sexuality": 1, + "mmlu_humanities": 1, + "mmlu_international_law": 1, + "mmlu_jurisprudence": 1, + "mmlu_logical_fallacies": 1, + "mmlu_machine_learning": 1, + "mmlu_management": 1, + "mmlu_marketing": 1, + "mmlu_medical_genetics": 1, + "mmlu_miscellaneous": 1, + "mmlu_moral_disputes": 1, + "mmlu_moral_scenarios": 1, + "mmlu_nutrition": 1, + "mmlu_other": 1, + "mmlu_philosophy": 1, + "mmlu_prehistory": 1, + "mmlu_professional_accounting": 1, + "mmlu_professional_law": 1, + "mmlu_professional_medicine": 1, + "mmlu_professional_psychology": 1, + "mmlu_public_relations": 1, + "mmlu_security_studies": 1, + "mmlu_social_sciences": 1, + "mmlu_sociology": 1, + "mmlu_stem": 1, + "mmlu_us_foreign_policy": 1, + "mmlu_virology": 1, + "mmlu_world_religions": 1 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 8 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..f6c8592fa4ef8d4c9fb094a8b1a31cbbe9daaaab --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:768cc781ddadfc2facadcf85ce04baf47884a6afe7a9cef096723cbc2f33ec79 +size 202406 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..9f2ff31d4f758bb77f83147a104daea13ca43087 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fc6c38be49f0b3b4a03fedc0a1410bfeaf269992fc95176221e69320d9cafbc0 +size 4479812 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..5661ec0ad12357a8f22a7b96c0a96fcde0200085 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json @@ -0,0 +1,2651 @@ +{ + "results": { + "mmlu": { + "acc,none": 0.30558325024925226, + "acc_stderr,none": 0.05316561692035, + "alias": "mmlu" + }, + "mmlu_humanities": { + "alias": " - humanities", + "acc,none": 0.2945802337938363, + "acc_stderr,none": 0.052104989652710335 + }, + "mmlu_formal_logic": { + "alias": " - formal_logic", + "acc,none": 0.29365079365079366, + "acc_stderr,none": 0.04073524322147126 + }, + "mmlu_high_school_european_history": { + "alias": " - high_school_european_history", + "acc,none": 0.41818181818181815, + "acc_stderr,none": 0.03851716319398395 + }, + "mmlu_high_school_us_history": { + "alias": " - high_school_us_history", + "acc,none": 0.3382352941176471, + "acc_stderr,none": 0.03320574612945432 + }, + "mmlu_high_school_world_history": { + "alias": " - high_school_world_history", + "acc,none": 0.3924050632911392, + "acc_stderr,none": 0.03178471874564729 + }, + "mmlu_international_law": { + "alias": " - international_law", + "acc,none": 0.2809917355371901, + "acc_stderr,none": 0.04103203830514512 + }, + "mmlu_jurisprudence": { + "alias": " - jurisprudence", + "acc,none": 0.3425925925925926, + "acc_stderr,none": 0.045879047413018105 + }, + "mmlu_logical_fallacies": { + "alias": " - logical_fallacies", + "acc,none": 0.25766871165644173, + "acc_stderr,none": 0.03436150827846917 + }, + "mmlu_moral_disputes": { + "alias": " - moral_disputes", + "acc,none": 0.3236994219653179, + "acc_stderr,none": 0.025190181327608422 + }, + "mmlu_moral_scenarios": { + "alias": " - moral_scenarios", + "acc,none": 0.23575418994413408, + "acc_stderr,none": 0.014196375686290804 + }, + "mmlu_philosophy": { + "alias": " - philosophy", + "acc,none": 0.28938906752411575, + "acc_stderr,none": 0.025755865922632924 + }, + "mmlu_prehistory": { + "alias": " - prehistory", + "acc,none": 0.36419753086419754, + "acc_stderr,none": 0.026774929899722334 + }, + "mmlu_professional_law": { + "alias": " - professional_law", + "acc,none": 0.26597131681877445, + "acc_stderr,none": 0.011285033165551276 + }, + "mmlu_world_religions": { + "alias": " - world_religions", + "acc,none": 0.38596491228070173, + "acc_stderr,none": 0.03733756969066164 + }, + "mmlu_other": { + "alias": " - other", + "acc,none": 0.3118764081107178, + "acc_stderr,none": 0.036246652839496706 + }, + "mmlu_business_ethics": { + "alias": " - business_ethics", + "acc,none": 0.31, + "acc_stderr,none": 0.046482319871173156 + }, + "mmlu_clinical_knowledge": { + "alias": " - clinical_knowledge", + "acc,none": 0.30943396226415093, + "acc_stderr,none": 0.028450154794118627 + }, + "mmlu_college_medicine": { + "alias": " - college_medicine", + "acc,none": 0.24855491329479767, + "acc_stderr,none": 0.03295304696818318 + }, + "mmlu_global_facts": { + "alias": " - global_facts", + "acc,none": 0.32, + "acc_stderr,none": 0.046882617226215034 + }, + "mmlu_human_aging": { + "alias": " - human_aging", + "acc,none": 0.3004484304932735, + "acc_stderr,none": 0.030769352008229136 + }, + "mmlu_management": { + "alias": " - management", + "acc,none": 0.3300970873786408, + "acc_stderr,none": 0.0465614711001235 + }, + "mmlu_marketing": { + "alias": " - marketing", + "acc,none": 0.36324786324786323, + "acc_stderr,none": 0.03150712523091264 + }, + "mmlu_medical_genetics": { + "alias": " - medical_genetics", + "acc,none": 0.3, + "acc_stderr,none": 0.046056618647183814 + }, + "mmlu_miscellaneous": { + "alias": " - miscellaneous", + "acc,none": 0.31800766283524906, + "acc_stderr,none": 0.016653486275615394 + }, + "mmlu_nutrition": { + "alias": " - nutrition", + "acc,none": 0.3300653594771242, + "acc_stderr,none": 0.02692565465361569 + }, + "mmlu_professional_accounting": { + "alias": " - professional_accounting", + "acc,none": 0.25886524822695034, + "acc_stderr,none": 0.026129572527180848 + }, + "mmlu_professional_medicine": { + "alias": " - professional_medicine", + "acc,none": 0.3125, + "acc_stderr,none": 0.02815637344037142 + }, + "mmlu_virology": { + "alias": " - virology", + "acc,none": 0.3433734939759036, + "acc_stderr,none": 0.03696584317010601 + }, + "mmlu_social_sciences": { + "alias": " - social_sciences", + "acc,none": 0.31979200519987006, + "acc_stderr,none": 0.0561340687383002 + }, + "mmlu_econometrics": { + "alias": " - econometrics", + "acc,none": 0.2543859649122807, + "acc_stderr,none": 0.040969851398436716 + }, + "mmlu_high_school_geography": { + "alias": " - high_school_geography", + "acc,none": 0.36363636363636365, + "acc_stderr,none": 0.03427308652999936 + }, + "mmlu_high_school_government_and_politics": { + "alias": " - high_school_government_and_politics", + "acc,none": 0.29533678756476683, + "acc_stderr,none": 0.03292296639155139 + }, + "mmlu_high_school_macroeconomics": { + "alias": " - high_school_macroeconomics", + "acc,none": 0.3128205128205128, + "acc_stderr,none": 0.023507579020645365 + }, + "mmlu_high_school_microeconomics": { + "alias": " - high_school_microeconomics", + "acc,none": 0.25210084033613445, + "acc_stderr,none": 0.02820554503327773 + }, + "mmlu_high_school_psychology": { + "alias": " - high_school_psychology", + "acc,none": 0.29357798165137616, + "acc_stderr,none": 0.01952515112263966 + }, + "mmlu_human_sexuality": { + "alias": " - human_sexuality", + "acc,none": 0.4198473282442748, + "acc_stderr,none": 0.04328577215262972 + }, + "mmlu_professional_psychology": { + "alias": " - professional_psychology", + "acc,none": 0.28431372549019607, + "acc_stderr,none": 0.01824902441120767 + }, + "mmlu_public_relations": { + "alias": " - public_relations", + "acc,none": 0.35454545454545455, + "acc_stderr,none": 0.045820048415054174 + }, + "mmlu_security_studies": { + "alias": " - security_studies", + "acc,none": 0.4489795918367347, + "acc_stderr,none": 0.03184213866687579 + }, + "mmlu_sociology": { + "alias": " - sociology", + "acc,none": 0.34328358208955223, + "acc_stderr,none": 0.03357379665433431 + }, + "mmlu_us_foreign_policy": { + "alias": " - us_foreign_policy", + "acc,none": 0.37, + "acc_stderr,none": 0.048523658709391 + }, + "mmlu_stem": { + "alias": " - stem", + "acc,none": 0.30193466539803365, + "acc_stderr,none": 0.06327068110464068 + }, + "mmlu_abstract_algebra": { + "alias": " - abstract_algebra", + "acc,none": 0.24, + "acc_stderr,none": 0.04292346959909283 + }, + "mmlu_anatomy": { + "alias": " - anatomy", + "acc,none": 0.3333333333333333, + "acc_stderr,none": 0.04072314811876837 + }, + "mmlu_astronomy": { + "alias": " - astronomy", + "acc,none": 0.3618421052631579, + "acc_stderr,none": 0.03910525752849725 + }, + "mmlu_college_biology": { + "alias": " - college_biology", + "acc,none": 0.3680555555555556, + "acc_stderr,none": 0.04032999053960719 + }, + "mmlu_college_chemistry": { + "alias": " - college_chemistry", + "acc,none": 0.41, + "acc_stderr,none": 0.04943110704237102 + }, + "mmlu_college_computer_science": { + "alias": " - college_computer_science", + "acc,none": 0.35, + "acc_stderr,none": 0.04793724854411018 + }, + "mmlu_college_mathematics": { + "alias": " - college_mathematics", + "acc,none": 0.28, + "acc_stderr,none": 0.04512608598542127 + }, + "mmlu_college_physics": { + "alias": " - college_physics", + "acc,none": 0.22549019607843138, + "acc_stderr,none": 0.041583075330832865 + }, + "mmlu_computer_security": { + "alias": " - computer_security", + "acc,none": 0.35, + "acc_stderr,none": 0.0479372485441102 + }, + "mmlu_conceptual_physics": { + "alias": " - conceptual_physics", + "acc,none": 0.3574468085106383, + "acc_stderr,none": 0.03132941789476425 + }, + "mmlu_electrical_engineering": { + "alias": " - electrical_engineering", + "acc,none": 0.32413793103448274, + "acc_stderr,none": 0.03900432069185554 + }, + "mmlu_elementary_mathematics": { + "alias": " - elementary_mathematics", + "acc,none": 0.2751322751322751, + "acc_stderr,none": 0.023000086859068646 + }, + "mmlu_high_school_biology": { + "alias": " - high_school_biology", + "acc,none": 0.3741935483870968, + "acc_stderr,none": 0.02752890429984578 + }, + "mmlu_high_school_chemistry": { + "alias": " - high_school_chemistry", + "acc,none": 0.29064039408866993, + "acc_stderr,none": 0.0319474007226554 + }, + "mmlu_high_school_computer_science": { + "alias": " - high_school_computer_science", + "acc,none": 0.28, + "acc_stderr,none": 0.04512608598542128 + }, + "mmlu_high_school_mathematics": { + "alias": " - high_school_mathematics", + "acc,none": 0.26296296296296295, + "acc_stderr,none": 0.026842057873833706 + }, + "mmlu_high_school_physics": { + "alias": " - high_school_physics", + "acc,none": 0.2119205298013245, + "acc_stderr,none": 0.03336767086567977 + }, + "mmlu_high_school_statistics": { + "alias": " - high_school_statistics", + "acc,none": 0.2175925925925926, + "acc_stderr,none": 0.028139689444859683 + }, + "mmlu_machine_learning": { + "alias": " - machine_learning", + "acc,none": 0.22321428571428573, + "acc_stderr,none": 0.039523019677025116 + } + }, + "groups": { + "mmlu": { + "acc,none": 0.30558325024925226, + "acc_stderr,none": 0.05316561692035, + "alias": "mmlu" + }, + "mmlu_humanities": { + "alias": " - humanities", + "acc,none": 0.2945802337938363, + "acc_stderr,none": 0.052104989652710335 + }, + "mmlu_other": { + "alias": " - other", + "acc,none": 0.3118764081107178, + "acc_stderr,none": 0.036246652839496706 + }, + "mmlu_social_sciences": { + "alias": " - social_sciences", + "acc,none": 0.31979200519987006, + "acc_stderr,none": 0.0561340687383002 + }, + "mmlu_stem": { + "alias": " - stem", + "acc,none": 0.30193466539803365, + "acc_stderr,none": 0.06327068110464068 + } + }, + "configs": { + "mmlu_abstract_algebra": { + "task": "mmlu_abstract_algebra", + "task_alias": "abstract_algebra", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "abstract_algebra", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_anatomy": { + "task": "mmlu_anatomy", + "task_alias": "anatomy", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "anatomy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about anatomy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_astronomy": { + "task": "mmlu_astronomy", + "task_alias": "astronomy", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "astronomy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about astronomy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_business_ethics": { + "task": "mmlu_business_ethics", + "task_alias": "business_ethics", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "business_ethics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about business ethics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_clinical_knowledge": { + "task": "mmlu_clinical_knowledge", + "task_alias": "clinical_knowledge", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "clinical_knowledge", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_biology": { + "task": "mmlu_college_biology", + "task_alias": "college_biology", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_biology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college biology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_chemistry": { + "task": "mmlu_college_chemistry", + "task_alias": "college_chemistry", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_chemistry", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_computer_science": { + "task": "mmlu_college_computer_science", + "task_alias": "college_computer_science", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_computer_science", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college computer science.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_mathematics": { + "task": "mmlu_college_mathematics", + "task_alias": "college_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_medicine": { + "task": "mmlu_college_medicine", + "task_alias": "college_medicine", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_medicine", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college medicine.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_physics": { + "task": "mmlu_college_physics", + "task_alias": "college_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_computer_security": { + "task": "mmlu_computer_security", + "task_alias": "computer_security", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "computer_security", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about computer security.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_conceptual_physics": { + "task": "mmlu_conceptual_physics", + "task_alias": "conceptual_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "conceptual_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_econometrics": { + "task": "mmlu_econometrics", + "task_alias": "econometrics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "econometrics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about econometrics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_electrical_engineering": { + "task": "mmlu_electrical_engineering", + "task_alias": "electrical_engineering", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "electrical_engineering", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_elementary_mathematics": { + "task": "mmlu_elementary_mathematics", + "task_alias": "elementary_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "elementary_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_formal_logic": { + "task": "mmlu_formal_logic", + "task_alias": "formal_logic", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "formal_logic", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about formal logic.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_global_facts": { + "task": "mmlu_global_facts", + "task_alias": "global_facts", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "global_facts", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about global facts.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_biology": { + "task": "mmlu_high_school_biology", + "task_alias": "high_school_biology", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_biology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school biology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_chemistry": { + "task": "mmlu_high_school_chemistry", + "task_alias": "high_school_chemistry", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_chemistry", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_computer_science": { + "task": "mmlu_high_school_computer_science", + "task_alias": "high_school_computer_science", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_computer_science", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_european_history": { + "task": "mmlu_high_school_european_history", + "task_alias": "high_school_european_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_european_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school european history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_geography": { + "task": "mmlu_high_school_geography", + "task_alias": "high_school_geography", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_geography", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school geography.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_government_and_politics": { + "task": "mmlu_high_school_government_and_politics", + "task_alias": "high_school_government_and_politics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_government_and_politics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_macroeconomics": { + "task": "mmlu_high_school_macroeconomics", + "task_alias": "high_school_macroeconomics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_macroeconomics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_mathematics": { + "task": "mmlu_high_school_mathematics", + "task_alias": "high_school_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_microeconomics": { + "task": "mmlu_high_school_microeconomics", + "task_alias": "high_school_microeconomics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_microeconomics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_physics": { + "task": "mmlu_high_school_physics", + "task_alias": "high_school_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_psychology": { + "task": "mmlu_high_school_psychology", + "task_alias": "high_school_psychology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_psychology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_statistics": { + "task": "mmlu_high_school_statistics", + "task_alias": "high_school_statistics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_statistics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_us_history": { + "task": "mmlu_high_school_us_history", + "task_alias": "high_school_us_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_us_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school us history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_world_history": { + "task": "mmlu_high_school_world_history", + "task_alias": "high_school_world_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_world_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school world history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_human_aging": { + "task": "mmlu_human_aging", + "task_alias": "human_aging", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "human_aging", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about human aging.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_human_sexuality": { + "task": "mmlu_human_sexuality", + "task_alias": "human_sexuality", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "human_sexuality", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_international_law": { + "task": "mmlu_international_law", + "task_alias": "international_law", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "international_law", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about international law.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_jurisprudence": { + "task": "mmlu_jurisprudence", + "task_alias": "jurisprudence", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "jurisprudence", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_logical_fallacies": { + "task": "mmlu_logical_fallacies", + "task_alias": "logical_fallacies", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "logical_fallacies", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_machine_learning": { + "task": "mmlu_machine_learning", + "task_alias": "machine_learning", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "machine_learning", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about machine learning.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_management": { + "task": "mmlu_management", + "task_alias": "management", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "management", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about management.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_marketing": { + "task": "mmlu_marketing", + "task_alias": "marketing", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "marketing", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about marketing.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_medical_genetics": { + "task": "mmlu_medical_genetics", + "task_alias": "medical_genetics", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "medical_genetics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_miscellaneous": { + "task": "mmlu_miscellaneous", + "task_alias": "miscellaneous", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "miscellaneous", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_moral_disputes": { + "task": "mmlu_moral_disputes", + "task_alias": "moral_disputes", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "moral_disputes", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_moral_scenarios": { + "task": "mmlu_moral_scenarios", + "task_alias": "moral_scenarios", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "moral_scenarios", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_nutrition": { + "task": "mmlu_nutrition", + "task_alias": "nutrition", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "nutrition", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about nutrition.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_philosophy": { + "task": "mmlu_philosophy", + "task_alias": "philosophy", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "philosophy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about philosophy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_prehistory": { + "task": "mmlu_prehistory", + "task_alias": "prehistory", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "prehistory", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about prehistory.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_accounting": { + "task": "mmlu_professional_accounting", + "task_alias": "professional_accounting", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_accounting", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_law": { + "task": "mmlu_professional_law", + "task_alias": "professional_law", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_law", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional law.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_medicine": { + "task": "mmlu_professional_medicine", + "task_alias": "professional_medicine", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_medicine", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_psychology": { + "task": "mmlu_professional_psychology", + "task_alias": "professional_psychology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_psychology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_public_relations": { + "task": "mmlu_public_relations", + "task_alias": "public_relations", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "public_relations", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about public relations.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_security_studies": { + "task": "mmlu_security_studies", + "task_alias": "security_studies", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "security_studies", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about security studies.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_sociology": { + "task": "mmlu_sociology", + "task_alias": "sociology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "sociology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about sociology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_us_foreign_policy": { + "task": "mmlu_us_foreign_policy", + "task_alias": "us_foreign_policy", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "us_foreign_policy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_virology": { + "task": "mmlu_virology", + "task_alias": "virology", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "virology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about virology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_world_religions": { + "task": "mmlu_world_religions", + "task_alias": "world_religions", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "world_religions", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about world religions.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + } + }, + "versions": { + "mmlu": "N/A", + "mmlu_abstract_algebra": 0.0, + "mmlu_anatomy": 0.0, + "mmlu_astronomy": 0.0, + "mmlu_business_ethics": 0.0, + "mmlu_clinical_knowledge": 0.0, + "mmlu_college_biology": 0.0, + "mmlu_college_chemistry": 0.0, + "mmlu_college_computer_science": 0.0, + "mmlu_college_mathematics": 0.0, + "mmlu_college_medicine": 0.0, + "mmlu_college_physics": 0.0, + "mmlu_computer_security": 0.0, + "mmlu_conceptual_physics": 0.0, + "mmlu_econometrics": 0.0, + "mmlu_electrical_engineering": 0.0, + "mmlu_elementary_mathematics": 0.0, + "mmlu_formal_logic": 0.0, + "mmlu_global_facts": 0.0, + "mmlu_high_school_biology": 0.0, + "mmlu_high_school_chemistry": 0.0, + "mmlu_high_school_computer_science": 0.0, + "mmlu_high_school_european_history": 0.0, + "mmlu_high_school_geography": 0.0, + "mmlu_high_school_government_and_politics": 0.0, + "mmlu_high_school_macroeconomics": 0.0, + "mmlu_high_school_mathematics": 0.0, + "mmlu_high_school_microeconomics": 0.0, + "mmlu_high_school_physics": 0.0, + "mmlu_high_school_psychology": 0.0, + "mmlu_high_school_statistics": 0.0, + "mmlu_high_school_us_history": 0.0, + "mmlu_high_school_world_history": 0.0, + "mmlu_human_aging": 0.0, + "mmlu_human_sexuality": 0.0, + "mmlu_humanities": "N/A", + "mmlu_international_law": 0.0, + "mmlu_jurisprudence": 0.0, + "mmlu_logical_fallacies": 0.0, + "mmlu_machine_learning": 0.0, + "mmlu_management": 0.0, + "mmlu_marketing": 0.0, + "mmlu_medical_genetics": 0.0, + "mmlu_miscellaneous": 0.0, + "mmlu_moral_disputes": 0.0, + "mmlu_moral_scenarios": 0.0, + "mmlu_nutrition": 0.0, + "mmlu_other": "N/A", + "mmlu_philosophy": 0.0, + "mmlu_prehistory": 0.0, + "mmlu_professional_accounting": 0.0, + "mmlu_professional_law": 0.0, + "mmlu_professional_medicine": 0.0, + "mmlu_professional_psychology": 0.0, + "mmlu_public_relations": 0.0, + "mmlu_security_studies": 0.0, + "mmlu_social_sciences": "N/A", + "mmlu_sociology": 0.0, + "mmlu_stem": "N/A", + "mmlu_us_foreign_policy": 0.0, + "mmlu_virology": 0.0, + "mmlu_world_religions": 0.0 + }, + "n-shot": { + "mmlu": 0, + "mmlu_abstract_algebra": 2, + "mmlu_anatomy": 2, + "mmlu_astronomy": 2, + "mmlu_business_ethics": 2, + "mmlu_clinical_knowledge": 2, + "mmlu_college_biology": 2, + "mmlu_college_chemistry": 2, + "mmlu_college_computer_science": 2, + "mmlu_college_mathematics": 2, + "mmlu_college_medicine": 2, + "mmlu_college_physics": 2, + "mmlu_computer_security": 2, + "mmlu_conceptual_physics": 2, + "mmlu_econometrics": 2, + "mmlu_electrical_engineering": 2, + "mmlu_elementary_mathematics": 2, + "mmlu_formal_logic": 2, + "mmlu_global_facts": 2, + "mmlu_high_school_biology": 2, + "mmlu_high_school_chemistry": 2, + "mmlu_high_school_computer_science": 2, + "mmlu_high_school_european_history": 2, + "mmlu_high_school_geography": 2, + "mmlu_high_school_government_and_politics": 2, + "mmlu_high_school_macroeconomics": 2, + "mmlu_high_school_mathematics": 2, + "mmlu_high_school_microeconomics": 2, + "mmlu_high_school_physics": 2, + "mmlu_high_school_psychology": 2, + "mmlu_high_school_statistics": 2, + "mmlu_high_school_us_history": 2, + "mmlu_high_school_world_history": 2, + "mmlu_human_aging": 2, + "mmlu_human_sexuality": 2, + "mmlu_humanities": 2, + "mmlu_international_law": 2, + "mmlu_jurisprudence": 2, + "mmlu_logical_fallacies": 2, + "mmlu_machine_learning": 2, + "mmlu_management": 2, + "mmlu_marketing": 2, + "mmlu_medical_genetics": 2, + "mmlu_miscellaneous": 2, + "mmlu_moral_disputes": 2, + "mmlu_moral_scenarios": 2, + "mmlu_nutrition": 2, + "mmlu_other": 2, + "mmlu_philosophy": 2, + "mmlu_prehistory": 2, + "mmlu_professional_accounting": 2, + "mmlu_professional_law": 2, + "mmlu_professional_medicine": 2, + "mmlu_professional_psychology": 2, + "mmlu_public_relations": 2, + "mmlu_security_studies": 2, + "mmlu_social_sciences": 2, + "mmlu_sociology": 2, + "mmlu_stem": 2, + "mmlu_us_foreign_policy": 2, + "mmlu_virology": 2, + "mmlu_world_religions": 2 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 8 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..7163ef9cfe0f85915eb90a88de083f496c96a5ea --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:653b4afd25e0e3e9fa7716f743147cf2c219299fc0efee2306bb8e9f48cbab13 +size 202466 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..93a3e99ab42f747bf7a689515f4a495b3900075c --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f194d5957525fefb1ced73d0b7ee43d7297ab702b1391f1a50b5c30b132922bb +size 5383261 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..70407e959f1678c7ce3235811733ceda3e9710a2 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json @@ -0,0 +1,2651 @@ +{ + "results": { + "mmlu": { + "acc,none": 0.30864549209514314, + "acc_stderr,none": 0.05140559934324045, + "alias": "mmlu" + }, + "mmlu_humanities": { + "alias": " - humanities", + "acc,none": 0.29436769394261425, + "acc_stderr,none": 0.04497916575062463 + }, + "mmlu_formal_logic": { + "alias": " - formal_logic", + "acc,none": 0.30952380952380953, + "acc_stderr,none": 0.04134913018303316 + }, + "mmlu_high_school_european_history": { + "alias": " - high_school_european_history", + "acc,none": 0.38181818181818183, + "acc_stderr,none": 0.03793713171165635 + }, + "mmlu_high_school_us_history": { + "alias": " - high_school_us_history", + "acc,none": 0.30392156862745096, + "acc_stderr,none": 0.03228210387037894 + }, + "mmlu_high_school_world_history": { + "alias": " - high_school_world_history", + "acc,none": 0.37130801687763715, + "acc_stderr,none": 0.03145068600744859 + }, + "mmlu_international_law": { + "alias": " - international_law", + "acc,none": 0.2809917355371901, + "acc_stderr,none": 0.04103203830514512 + }, + "mmlu_jurisprudence": { + "alias": " - jurisprudence", + "acc,none": 0.3148148148148148, + "acc_stderr,none": 0.04489931073591311 + }, + "mmlu_logical_fallacies": { + "alias": " - logical_fallacies", + "acc,none": 0.3619631901840491, + "acc_stderr,none": 0.037757007291414416 + }, + "mmlu_moral_disputes": { + "alias": " - moral_disputes", + "acc,none": 0.315028901734104, + "acc_stderr,none": 0.025009313790069706 + }, + "mmlu_moral_scenarios": { + "alias": " - moral_scenarios", + "acc,none": 0.24134078212290502, + "acc_stderr,none": 0.01431099954796147 + }, + "mmlu_philosophy": { + "alias": " - philosophy", + "acc,none": 0.2604501607717042, + "acc_stderr,none": 0.02492672322484555 + }, + "mmlu_prehistory": { + "alias": " - prehistory", + "acc,none": 0.30864197530864196, + "acc_stderr,none": 0.025702640260603746 + }, + "mmlu_professional_law": { + "alias": " - professional_law", + "acc,none": 0.2816166883963494, + "acc_stderr,none": 0.011487783272786696 + }, + "mmlu_world_religions": { + "alias": " - world_religions", + "acc,none": 0.39766081871345027, + "acc_stderr,none": 0.0375363895576169 + }, + "mmlu_other": { + "alias": " - other", + "acc,none": 0.34502735757965886, + "acc_stderr,none": 0.03902835053815799 + }, + "mmlu_business_ethics": { + "alias": " - business_ethics", + "acc,none": 0.36, + "acc_stderr,none": 0.048241815132442176 + }, + "mmlu_clinical_knowledge": { + "alias": " - clinical_knowledge", + "acc,none": 0.33962264150943394, + "acc_stderr,none": 0.02914690474779833 + }, + "mmlu_college_medicine": { + "alias": " - college_medicine", + "acc,none": 0.30057803468208094, + "acc_stderr,none": 0.0349610148119118 + }, + "mmlu_global_facts": { + "alias": " - global_facts", + "acc,none": 0.34, + "acc_stderr,none": 0.04760952285695235 + }, + "mmlu_human_aging": { + "alias": " - human_aging", + "acc,none": 0.32286995515695066, + "acc_stderr,none": 0.03138147637575498 + }, + "mmlu_management": { + "alias": " - management", + "acc,none": 0.3300970873786408, + "acc_stderr,none": 0.04656147110012351 + }, + "mmlu_marketing": { + "alias": " - marketing", + "acc,none": 0.3418803418803419, + "acc_stderr,none": 0.031075028526507745 + }, + "mmlu_medical_genetics": { + "alias": " - medical_genetics", + "acc,none": 0.28, + "acc_stderr,none": 0.04512608598542127 + }, + "mmlu_miscellaneous": { + "alias": " - miscellaneous", + "acc,none": 0.39080459770114945, + "acc_stderr,none": 0.01744836606706253 + }, + "mmlu_nutrition": { + "alias": " - nutrition", + "acc,none": 0.369281045751634, + "acc_stderr,none": 0.027634176689602663 + }, + "mmlu_professional_accounting": { + "alias": " - professional_accounting", + "acc,none": 0.2872340425531915, + "acc_stderr,none": 0.026992199173064356 + }, + "mmlu_professional_medicine": { + "alias": " - professional_medicine", + "acc,none": 0.3602941176470588, + "acc_stderr,none": 0.029163128570670736 + }, + "mmlu_virology": { + "alias": " - virology", + "acc,none": 0.2891566265060241, + "acc_stderr,none": 0.03529486801511115 + }, + "mmlu_social_sciences": { + "alias": " - social_sciences", + "acc,none": 0.3207669808254794, + "acc_stderr,none": 0.05347677675318793 + }, + "mmlu_econometrics": { + "alias": " - econometrics", + "acc,none": 0.2807017543859649, + "acc_stderr,none": 0.04227054451232199 + }, + "mmlu_high_school_geography": { + "alias": " - high_school_geography", + "acc,none": 0.2222222222222222, + "acc_stderr,none": 0.029620227874790482 + }, + "mmlu_high_school_government_and_politics": { + "alias": " - high_school_government_and_politics", + "acc,none": 0.36787564766839376, + "acc_stderr,none": 0.03480175668466036 + }, + "mmlu_high_school_macroeconomics": { + "alias": " - high_school_macroeconomics", + "acc,none": 0.3435897435897436, + "acc_stderr,none": 0.024078696580635484 + }, + "mmlu_high_school_microeconomics": { + "alias": " - high_school_microeconomics", + "acc,none": 0.2605042016806723, + "acc_stderr,none": 0.02851025151234193 + }, + "mmlu_high_school_psychology": { + "alias": " - high_school_psychology", + "acc,none": 0.3155963302752294, + "acc_stderr,none": 0.019926117513869662 + }, + "mmlu_human_sexuality": { + "alias": " - human_sexuality", + "acc,none": 0.3969465648854962, + "acc_stderr,none": 0.04291135671009225 + }, + "mmlu_professional_psychology": { + "alias": " - professional_psychology", + "acc,none": 0.2761437908496732, + "acc_stderr,none": 0.018087276935663137 + }, + "mmlu_public_relations": { + "alias": " - public_relations", + "acc,none": 0.33636363636363636, + "acc_stderr,none": 0.04525393596302505 + }, + "mmlu_security_studies": { + "alias": " - security_studies", + "acc,none": 0.4, + "acc_stderr,none": 0.03136250240935893 + }, + "mmlu_sociology": { + "alias": " - sociology", + "acc,none": 0.3880597014925373, + "acc_stderr,none": 0.0344578996436275 + }, + "mmlu_us_foreign_policy": { + "alias": " - us_foreign_policy", + "acc,none": 0.38, + "acc_stderr,none": 0.04878317312145633 + }, + "mmlu_stem": { + "alias": " - stem", + "acc,none": 0.28227085315572475, + "acc_stderr,none": 0.05646604183126475 + }, + "mmlu_abstract_algebra": { + "alias": " - abstract_algebra", + "acc,none": 0.2, + "acc_stderr,none": 0.04020151261036843 + }, + "mmlu_anatomy": { + "alias": " - anatomy", + "acc,none": 0.26666666666666666, + "acc_stderr,none": 0.038201699145179055 + }, + "mmlu_astronomy": { + "alias": " - astronomy", + "acc,none": 0.3684210526315789, + "acc_stderr,none": 0.03925523381052932 + }, + "mmlu_college_biology": { + "alias": " - college_biology", + "acc,none": 0.3125, + "acc_stderr,none": 0.038760854559127644 + }, + "mmlu_college_chemistry": { + "alias": " - college_chemistry", + "acc,none": 0.32, + "acc_stderr,none": 0.04688261722621504 + }, + "mmlu_college_computer_science": { + "alias": " - college_computer_science", + "acc,none": 0.32, + "acc_stderr,none": 0.04688261722621504 + }, + "mmlu_college_mathematics": { + "alias": " - college_mathematics", + "acc,none": 0.29, + "acc_stderr,none": 0.04560480215720683 + }, + "mmlu_college_physics": { + "alias": " - college_physics", + "acc,none": 0.18627450980392157, + "acc_stderr,none": 0.038739587141493524 + }, + "mmlu_computer_security": { + "alias": " - computer_security", + "acc,none": 0.37, + "acc_stderr,none": 0.04852365870939099 + }, + "mmlu_conceptual_physics": { + "alias": " - conceptual_physics", + "acc,none": 0.3191489361702128, + "acc_stderr,none": 0.030472973363380035 + }, + "mmlu_electrical_engineering": { + "alias": " - electrical_engineering", + "acc,none": 0.27586206896551724, + "acc_stderr,none": 0.037245636197746304 + }, + "mmlu_elementary_mathematics": { + "alias": " - elementary_mathematics", + "acc,none": 0.2830687830687831, + "acc_stderr,none": 0.023201392938194974 + }, + "mmlu_high_school_biology": { + "alias": " - high_school_biology", + "acc,none": 0.35161290322580646, + "acc_stderr,none": 0.02716253782694846 + }, + "mmlu_high_school_chemistry": { + "alias": " - high_school_chemistry", + "acc,none": 0.21674876847290642, + "acc_stderr,none": 0.02899033125251624 + }, + "mmlu_high_school_computer_science": { + "alias": " - high_school_computer_science", + "acc,none": 0.32, + "acc_stderr,none": 0.04688261722621505 + }, + "mmlu_high_school_mathematics": { + "alias": " - high_school_mathematics", + "acc,none": 0.24814814814814815, + "acc_stderr,none": 0.026335739404055803 + }, + "mmlu_high_school_physics": { + "alias": " - high_school_physics", + "acc,none": 0.2185430463576159, + "acc_stderr,none": 0.03374235550425694 + }, + "mmlu_high_school_statistics": { + "alias": " - high_school_statistics", + "acc,none": 0.22685185185185186, + "acc_stderr,none": 0.028561650102422252 + }, + "mmlu_machine_learning": { + "alias": " - machine_learning", + "acc,none": 0.25, + "acc_stderr,none": 0.04109974682633932 + } + }, + "groups": { + "mmlu": { + "acc,none": 0.30864549209514314, + "acc_stderr,none": 0.05140559934324045, + "alias": "mmlu" + }, + "mmlu_humanities": { + "alias": " - humanities", + "acc,none": 0.29436769394261425, + "acc_stderr,none": 0.04497916575062463 + }, + "mmlu_other": { + "alias": " - other", + "acc,none": 0.34502735757965886, + "acc_stderr,none": 0.03902835053815799 + }, + "mmlu_social_sciences": { + "alias": " - social_sciences", + "acc,none": 0.3207669808254794, + "acc_stderr,none": 0.05347677675318793 + }, + "mmlu_stem": { + "alias": " - stem", + "acc,none": 0.28227085315572475, + "acc_stderr,none": 0.05646604183126475 + } + }, + "configs": { + "mmlu_abstract_algebra": { + "task": "mmlu_abstract_algebra", + "task_alias": "abstract_algebra", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "abstract_algebra", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about abstract algebra.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_anatomy": { + "task": "mmlu_anatomy", + "task_alias": "anatomy", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "anatomy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about anatomy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_astronomy": { + "task": "mmlu_astronomy", + "task_alias": "astronomy", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "astronomy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about astronomy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_business_ethics": { + "task": "mmlu_business_ethics", + "task_alias": "business_ethics", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "business_ethics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about business ethics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_clinical_knowledge": { + "task": "mmlu_clinical_knowledge", + "task_alias": "clinical_knowledge", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "clinical_knowledge", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about clinical knowledge.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_biology": { + "task": "mmlu_college_biology", + "task_alias": "college_biology", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_biology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college biology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_chemistry": { + "task": "mmlu_college_chemistry", + "task_alias": "college_chemistry", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_chemistry", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college chemistry.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_computer_science": { + "task": "mmlu_college_computer_science", + "task_alias": "college_computer_science", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_computer_science", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college computer science.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_mathematics": { + "task": "mmlu_college_mathematics", + "task_alias": "college_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_medicine": { + "task": "mmlu_college_medicine", + "task_alias": "college_medicine", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_medicine", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college medicine.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_college_physics": { + "task": "mmlu_college_physics", + "task_alias": "college_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "college_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about college physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_computer_security": { + "task": "mmlu_computer_security", + "task_alias": "computer_security", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "computer_security", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about computer security.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_conceptual_physics": { + "task": "mmlu_conceptual_physics", + "task_alias": "conceptual_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "conceptual_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about conceptual physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_econometrics": { + "task": "mmlu_econometrics", + "task_alias": "econometrics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "econometrics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about econometrics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_electrical_engineering": { + "task": "mmlu_electrical_engineering", + "task_alias": "electrical_engineering", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "electrical_engineering", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about electrical engineering.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_elementary_mathematics": { + "task": "mmlu_elementary_mathematics", + "task_alias": "elementary_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "elementary_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about elementary mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_formal_logic": { + "task": "mmlu_formal_logic", + "task_alias": "formal_logic", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "formal_logic", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about formal logic.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_global_facts": { + "task": "mmlu_global_facts", + "task_alias": "global_facts", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "global_facts", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about global facts.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_biology": { + "task": "mmlu_high_school_biology", + "task_alias": "high_school_biology", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_biology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school biology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_chemistry": { + "task": "mmlu_high_school_chemistry", + "task_alias": "high_school_chemistry", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_chemistry", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school chemistry.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_computer_science": { + "task": "mmlu_high_school_computer_science", + "task_alias": "high_school_computer_science", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_computer_science", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school computer science.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_european_history": { + "task": "mmlu_high_school_european_history", + "task_alias": "high_school_european_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_european_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school european history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_geography": { + "task": "mmlu_high_school_geography", + "task_alias": "high_school_geography", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_geography", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school geography.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_government_and_politics": { + "task": "mmlu_high_school_government_and_politics", + "task_alias": "high_school_government_and_politics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_government_and_politics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school government and politics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_macroeconomics": { + "task": "mmlu_high_school_macroeconomics", + "task_alias": "high_school_macroeconomics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_macroeconomics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school macroeconomics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_mathematics": { + "task": "mmlu_high_school_mathematics", + "task_alias": "high_school_mathematics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_mathematics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school mathematics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_microeconomics": { + "task": "mmlu_high_school_microeconomics", + "task_alias": "high_school_microeconomics", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_microeconomics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school microeconomics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_physics": { + "task": "mmlu_high_school_physics", + "task_alias": "high_school_physics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_physics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school physics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_psychology": { + "task": "mmlu_high_school_psychology", + "task_alias": "high_school_psychology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_psychology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school psychology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_statistics": { + "task": "mmlu_high_school_statistics", + "task_alias": "high_school_statistics", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_statistics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school statistics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_us_history": { + "task": "mmlu_high_school_us_history", + "task_alias": "high_school_us_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_us_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school us history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_high_school_world_history": { + "task": "mmlu_high_school_world_history", + "task_alias": "high_school_world_history", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "high_school_world_history", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about high school world history.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_human_aging": { + "task": "mmlu_human_aging", + "task_alias": "human_aging", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "human_aging", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about human aging.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_human_sexuality": { + "task": "mmlu_human_sexuality", + "task_alias": "human_sexuality", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "human_sexuality", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about human sexuality.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_international_law": { + "task": "mmlu_international_law", + "task_alias": "international_law", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "international_law", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about international law.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_jurisprudence": { + "task": "mmlu_jurisprudence", + "task_alias": "jurisprudence", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "jurisprudence", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about jurisprudence.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_logical_fallacies": { + "task": "mmlu_logical_fallacies", + "task_alias": "logical_fallacies", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "logical_fallacies", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about logical fallacies.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_machine_learning": { + "task": "mmlu_machine_learning", + "task_alias": "machine_learning", + "group": "mmlu_stem", + "group_alias": "stem", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "machine_learning", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about machine learning.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_management": { + "task": "mmlu_management", + "task_alias": "management", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "management", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about management.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_marketing": { + "task": "mmlu_marketing", + "task_alias": "marketing", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "marketing", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about marketing.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_medical_genetics": { + "task": "mmlu_medical_genetics", + "task_alias": "medical_genetics", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "medical_genetics", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about medical genetics.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_miscellaneous": { + "task": "mmlu_miscellaneous", + "task_alias": "miscellaneous", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "miscellaneous", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about miscellaneous.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_moral_disputes": { + "task": "mmlu_moral_disputes", + "task_alias": "moral_disputes", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "moral_disputes", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about moral disputes.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_moral_scenarios": { + "task": "mmlu_moral_scenarios", + "task_alias": "moral_scenarios", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "moral_scenarios", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about moral scenarios.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_nutrition": { + "task": "mmlu_nutrition", + "task_alias": "nutrition", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "nutrition", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about nutrition.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_philosophy": { + "task": "mmlu_philosophy", + "task_alias": "philosophy", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "philosophy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about philosophy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_prehistory": { + "task": "mmlu_prehistory", + "task_alias": "prehistory", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "prehistory", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about prehistory.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_accounting": { + "task": "mmlu_professional_accounting", + "task_alias": "professional_accounting", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_accounting", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional accounting.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_law": { + "task": "mmlu_professional_law", + "task_alias": "professional_law", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_law", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional law.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_medicine": { + "task": "mmlu_professional_medicine", + "task_alias": "professional_medicine", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_medicine", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional medicine.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_professional_psychology": { + "task": "mmlu_professional_psychology", + "task_alias": "professional_psychology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "professional_psychology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about professional psychology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_public_relations": { + "task": "mmlu_public_relations", + "task_alias": "public_relations", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "public_relations", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about public relations.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_security_studies": { + "task": "mmlu_security_studies", + "task_alias": "security_studies", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "security_studies", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about security studies.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_sociology": { + "task": "mmlu_sociology", + "task_alias": "sociology", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "sociology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about sociology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_us_foreign_policy": { + "task": "mmlu_us_foreign_policy", + "task_alias": "us_foreign_policy", + "group": "mmlu_social_sciences", + "group_alias": "social_sciences", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "us_foreign_policy", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about us foreign policy.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_virology": { + "task": "mmlu_virology", + "task_alias": "virology", + "group": "mmlu_other", + "group_alias": "other", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "virology", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about virology.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "mmlu_world_religions": { + "task": "mmlu_world_religions", + "task_alias": "world_religions", + "group": "mmlu_humanities", + "group_alias": "humanities", + "dataset_path": "hails/mmlu_no_train", + "dataset_name": "world_religions", + "test_split": "test", + "fewshot_split": "dev", + "doc_to_text": "{{question.strip()}}\nA. {{choices[0]}}\nB. {{choices[1]}}\nC. {{choices[2]}}\nD. {{choices[3]}}\nAnswer:", + "doc_to_target": "answer", + "doc_to_choice": [ + "A", + "B", + "C", + "D" + ], + "description": "The following are multiple choice questions (with answers) about world religions.\n\n", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "fewshot_config": { + "sampler": "first_n" + }, + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + } + }, + "versions": { + "mmlu": "N/A", + "mmlu_abstract_algebra": 0.0, + "mmlu_anatomy": 0.0, + "mmlu_astronomy": 0.0, + "mmlu_business_ethics": 0.0, + "mmlu_clinical_knowledge": 0.0, + "mmlu_college_biology": 0.0, + "mmlu_college_chemistry": 0.0, + "mmlu_college_computer_science": 0.0, + "mmlu_college_mathematics": 0.0, + "mmlu_college_medicine": 0.0, + "mmlu_college_physics": 0.0, + "mmlu_computer_security": 0.0, + "mmlu_conceptual_physics": 0.0, + "mmlu_econometrics": 0.0, + "mmlu_electrical_engineering": 0.0, + "mmlu_elementary_mathematics": 0.0, + "mmlu_formal_logic": 0.0, + "mmlu_global_facts": 0.0, + "mmlu_high_school_biology": 0.0, + "mmlu_high_school_chemistry": 0.0, + "mmlu_high_school_computer_science": 0.0, + "mmlu_high_school_european_history": 0.0, + "mmlu_high_school_geography": 0.0, + "mmlu_high_school_government_and_politics": 0.0, + "mmlu_high_school_macroeconomics": 0.0, + "mmlu_high_school_mathematics": 0.0, + "mmlu_high_school_microeconomics": 0.0, + "mmlu_high_school_physics": 0.0, + "mmlu_high_school_psychology": 0.0, + "mmlu_high_school_statistics": 0.0, + "mmlu_high_school_us_history": 0.0, + "mmlu_high_school_world_history": 0.0, + "mmlu_human_aging": 0.0, + "mmlu_human_sexuality": 0.0, + "mmlu_humanities": "N/A", + "mmlu_international_law": 0.0, + "mmlu_jurisprudence": 0.0, + "mmlu_logical_fallacies": 0.0, + "mmlu_machine_learning": 0.0, + "mmlu_management": 0.0, + "mmlu_marketing": 0.0, + "mmlu_medical_genetics": 0.0, + "mmlu_miscellaneous": 0.0, + "mmlu_moral_disputes": 0.0, + "mmlu_moral_scenarios": 0.0, + "mmlu_nutrition": 0.0, + "mmlu_other": "N/A", + "mmlu_philosophy": 0.0, + "mmlu_prehistory": 0.0, + "mmlu_professional_accounting": 0.0, + "mmlu_professional_law": 0.0, + "mmlu_professional_medicine": 0.0, + "mmlu_professional_psychology": 0.0, + "mmlu_public_relations": 0.0, + "mmlu_security_studies": 0.0, + "mmlu_social_sciences": "N/A", + "mmlu_sociology": 0.0, + "mmlu_stem": "N/A", + "mmlu_us_foreign_policy": 0.0, + "mmlu_virology": 0.0, + "mmlu_world_religions": 0.0 + }, + "n-shot": { + "mmlu": 0, + "mmlu_abstract_algebra": 5, + "mmlu_anatomy": 5, + "mmlu_astronomy": 5, + "mmlu_business_ethics": 5, + "mmlu_clinical_knowledge": 5, + "mmlu_college_biology": 5, + "mmlu_college_chemistry": 5, + "mmlu_college_computer_science": 5, + "mmlu_college_mathematics": 5, + "mmlu_college_medicine": 5, + "mmlu_college_physics": 5, + "mmlu_computer_security": 5, + "mmlu_conceptual_physics": 5, + "mmlu_econometrics": 5, + "mmlu_electrical_engineering": 5, + "mmlu_elementary_mathematics": 5, + "mmlu_formal_logic": 5, + "mmlu_global_facts": 5, + "mmlu_high_school_biology": 5, + "mmlu_high_school_chemistry": 5, + "mmlu_high_school_computer_science": 5, + "mmlu_high_school_european_history": 5, + "mmlu_high_school_geography": 5, + "mmlu_high_school_government_and_politics": 5, + "mmlu_high_school_macroeconomics": 5, + "mmlu_high_school_mathematics": 5, + "mmlu_high_school_microeconomics": 5, + "mmlu_high_school_physics": 5, + "mmlu_high_school_psychology": 5, + "mmlu_high_school_statistics": 5, + "mmlu_high_school_us_history": 5, + "mmlu_high_school_world_history": 5, + "mmlu_human_aging": 5, + "mmlu_human_sexuality": 5, + "mmlu_humanities": 5, + "mmlu_international_law": 5, + "mmlu_jurisprudence": 5, + "mmlu_logical_fallacies": 5, + "mmlu_machine_learning": 5, + "mmlu_management": 5, + "mmlu_marketing": 5, + "mmlu_medical_genetics": 5, + "mmlu_miscellaneous": 5, + "mmlu_moral_disputes": 5, + "mmlu_moral_scenarios": 5, + "mmlu_nutrition": 5, + "mmlu_other": 5, + "mmlu_philosophy": 5, + "mmlu_prehistory": 5, + "mmlu_professional_accounting": 5, + "mmlu_professional_law": 5, + "mmlu_professional_medicine": 5, + "mmlu_professional_psychology": 5, + "mmlu_public_relations": 5, + "mmlu_security_studies": 5, + "mmlu_social_sciences": 5, + "mmlu_sociology": 5, + "mmlu_stem": 5, + "mmlu_us_foreign_policy": 5, + "mmlu_virology": 5, + "mmlu_world_religions": 5 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 8 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..d555e850f3736ce444a8d472c614ee0f44d95dcd --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/mmlu/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ab2df012db414dbfe58f18c2c07e7f37e0deb997e856a403d14c8ae4e50617e2 +size 202712 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..4b5e977a96383689e0290bf7972272c9ea0864a4 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bf5665a69b88801cfc3ac2b83778a7c81809436c0de8287a56f3b1073fffa048 +size 2133470 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..445f1f63d6053a6f9a3ba0a5c6446857c70d7239 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,283 @@ +{ + "results": { + "pawsx": { + "acc,none": 0.45671428571428574, + "acc_stderr,none": 0.04503688625601942, + "alias": "pawsx" + }, + "paws_de": { + "acc,none": 0.399, + "acc_stderr,none": 0.010952601505572451, + "alias": " - paws_de" + }, + "paws_en": { + "acc,none": 0.385, + "acc_stderr,none": 0.010883323176386975, + "alias": " - paws_en" + }, + "paws_es": { + "acc,none": 0.3725, + "acc_stderr,none": 0.010813433320184794, + "alias": " - paws_es" + }, + "paws_fr": { + "acc,none": 0.5395, + "acc_stderr,none": 0.011148184426533283, + "alias": " - paws_fr" + }, + "paws_ja": { + "acc,none": 0.5205, + "acc_stderr,none": 0.011173732641806813, + "alias": " - paws_ja" + }, + "paws_ko": { + "acc,none": 0.484, + "acc_stderr,none": 0.011177408788874896, + "alias": " - paws_ko" + }, + "paws_zh": { + "acc,none": 0.4965, + "acc_stderr,none": 0.011182862030875934, + "alias": " - paws_zh" + } + }, + "groups": { + "pawsx": { + "acc,none": 0.45671428571428574, + "acc_stderr,none": 0.04503688625601942, + "alias": "pawsx" + } + }, + "configs": { + "paws_de": { + "task": "paws_de", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "de", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", richtig? Ja, \"+sentence2, sentence1+\", richtig? Nein, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_en": { + "task": "paws_en", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "en", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", right? Yes, \"+sentence2, sentence1+\", right? No, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_es": { + "task": "paws_es", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "es", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", verdad? Sí, \"+sentence2, sentence1+\", verdad? No, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_fr": { + "task": "paws_fr", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "fr", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", n'est-ce pas? Oui, \"+sentence2, sentence1+\", n'est-ce pas? No, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_ja": { + "task": "paws_ja", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "ja", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", ですね? はい, \"+sentence2, sentence1+\", ですね? いいえ, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_ko": { + "task": "paws_ko", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "ko", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", 맞죠? 예, \"+sentence2, sentence1+\", 맞죠? 아니요, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_zh": { + "task": "paws_zh", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "zh", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", 对吧? 是, \"+sentence2, sentence1+\", 对吧? 不是, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + } + }, + "versions": { + "paws_de": 0.0, + "paws_en": 0.0, + "paws_es": 0.0, + "paws_fr": 0.0, + "paws_ja": 0.0, + "paws_ko": 0.0, + "paws_zh": 0.0, + "pawsx": "N/A" + }, + "n-shot": { + "paws_de": 0, + "paws_en": 0, + "paws_es": 0, + "paws_fr": 0, + "paws_ja": 0, + "paws_ko": 0, + "paws_zh": 0, + "pawsx": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..bb802fc4a74c1fe08d6c3b99ea9bb8953964f37f --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b0e09f39ef452dfb32888916f9ea0f3446ad84fa0a868665c56b4205872ca7f0 +size 58994 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..d723e0f1afe6908dc9cba7f5b353f5b29bcf2e35 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:102b25deb55b73448a30509a8085664e645712ecfef50ea86e018a2bd94bf927 +size 2127451 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..a9c9999803a22c4ac0e4d0795575218afdf967a9 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,283 @@ +{ + "results": { + "pawsx": { + "acc,none": 0.4555, + "acc_stderr,none": 0.05413647422159046, + "alias": "pawsx" + }, + "paws_de": { + "acc,none": 0.4, + "acc_stderr,none": 0.010957190790298967, + "alias": " - paws_de" + }, + "paws_en": { + "acc,none": 0.3765, + "acc_stderr,none": 0.010836631916589663, + "alias": " - paws_en" + }, + "paws_es": { + "acc,none": 0.3725, + "acc_stderr,none": 0.01081343332018479, + "alias": " - paws_es" + }, + "paws_fr": { + "acc,none": 0.5385, + "acc_stderr,none": 0.011149934327957061, + "alias": " - paws_fr" + }, + "paws_ja": { + "acc,none": 0.519, + "acc_stderr,none": 0.011175058879956061, + "alias": " - paws_ja" + }, + "paws_ko": { + "acc,none": 0.4845, + "acc_stderr,none": 0.01117776123260332, + "alias": " - paws_ko" + }, + "paws_zh": { + "acc,none": 0.4975, + "acc_stderr,none": 0.011182996230990788, + "alias": " - paws_zh" + } + }, + "groups": { + "pawsx": { + "acc,none": 0.4555, + "acc_stderr,none": 0.05413647422159046, + "alias": "pawsx" + } + }, + "configs": { + "paws_de": { + "task": "paws_de", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "de", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", richtig? Ja, \"+sentence2, sentence1+\", richtig? Nein, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_en": { + "task": "paws_en", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "en", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", right? Yes, \"+sentence2, sentence1+\", right? No, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_es": { + "task": "paws_es", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "es", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", verdad? Sí, \"+sentence2, sentence1+\", verdad? No, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_fr": { + "task": "paws_fr", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "fr", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", n'est-ce pas? Oui, \"+sentence2, sentence1+\", n'est-ce pas? No, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_ja": { + "task": "paws_ja", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "ja", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", ですね? はい, \"+sentence2, sentence1+\", ですね? いいえ, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_ko": { + "task": "paws_ko", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "ko", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", 맞죠? 예, \"+sentence2, sentence1+\", 맞죠? 아니요, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + }, + "paws_zh": { + "task": "paws_zh", + "group": "pawsx", + "dataset_path": "paws-x", + "dataset_name": "zh", + "training_split": "train", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[sentence1+\", 对吧? 是, \"+sentence2, sentence1+\", 对吧? 不是, \"+sentence2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 0.0 + } + } + }, + "versions": { + "paws_de": 0.0, + "paws_en": 0.0, + "paws_es": 0.0, + "paws_fr": 0.0, + "paws_ja": 0.0, + "paws_ko": 0.0, + "paws_zh": 0.0, + "pawsx": "N/A" + }, + "n-shot": { + "paws_de": 0, + "paws_en": 0, + "paws_es": 0, + "paws_fr": 0, + "paws_ja": 0, + "paws_ko": 0, + "paws_zh": 0, + "pawsx": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "c8d9bbd" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..014b6b27f9fa8bfb730c028ce6920122ca70f2e6 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/pawsx/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3f771eb5d9f76058ecad974ee3574b0abd76bbaea84b2bfa5633d14a53ccbc0c +size 30954 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..a2c4e19b3e9a57145bf758ff6158d06be26e9053 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:83e0ef2f6927c7e036a8da9c182acfeaf3fe1538163f0c550b7175c05bf6f1ec +size 263646 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..b2920a0fa849be2116a55b5a60422cc1a67d7423 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json @@ -0,0 +1,62 @@ +{ + "results": { + "truthfulqa_mc2": { + "acc,none": 0.406040041544547, + "acc_stderr,none": 0.014335281713396954, + "alias": "truthfulqa_mc2" + } + }, + "configs": { + "truthfulqa_mc2": { + "task": "truthfulqa_mc2", + "group": [ + "truthfulqa" + ], + "dataset_path": "truthful_qa", + "dataset_name": "multiple_choice", + "validation_split": "validation", + "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}", + "doc_to_target": 0, + "doc_to_choice": "{{mc2_targets.choices}}", + "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "question", + "metadata": { + "version": 2.0 + } + } + }, + "versions": { + "truthfulqa_mc2": 2.0 + }, + "n-shot": { + "truthfulqa_mc2": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..d7c7185a6516fbe06a601eef02b073e58965ab65 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e7199f071a8dfce909cb2ca95e819bd7cb724bb83ef39c48c7d13841f57a955a +size 42378 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..a2c4e19b3e9a57145bf758ff6158d06be26e9053 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:83e0ef2f6927c7e036a8da9c182acfeaf3fe1538163f0c550b7175c05bf6f1ec +size 263646 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..b2920a0fa849be2116a55b5a60422cc1a67d7423 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json @@ -0,0 +1,62 @@ +{ + "results": { + "truthfulqa_mc2": { + "acc,none": 0.406040041544547, + "acc_stderr,none": 0.014335281713396954, + "alias": "truthfulqa_mc2" + } + }, + "configs": { + "truthfulqa_mc2": { + "task": "truthfulqa_mc2", + "group": [ + "truthfulqa" + ], + "dataset_path": "truthful_qa", + "dataset_name": "multiple_choice", + "validation_split": "validation", + "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}", + "doc_to_target": 0, + "doc_to_choice": "{{mc2_targets.choices}}", + "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "question", + "metadata": { + "version": 2.0 + } + } + }, + "versions": { + "truthfulqa_mc2": 2.0 + }, + "n-shot": { + "truthfulqa_mc2": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..14afb8397402378da88a54ce79b89f4c2c187426 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0349b7bcef4c99a7bc0c2daab4f452952117622eafbec107a342ffcdfc1447c3 +size 42379 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..a2c4e19b3e9a57145bf758ff6158d06be26e9053 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:83e0ef2f6927c7e036a8da9c182acfeaf3fe1538163f0c550b7175c05bf6f1ec +size 263646 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..b2920a0fa849be2116a55b5a60422cc1a67d7423 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json @@ -0,0 +1,62 @@ +{ + "results": { + "truthfulqa_mc2": { + "acc,none": 0.406040041544547, + "acc_stderr,none": 0.014335281713396954, + "alias": "truthfulqa_mc2" + } + }, + "configs": { + "truthfulqa_mc2": { + "task": "truthfulqa_mc2", + "group": [ + "truthfulqa" + ], + "dataset_path": "truthful_qa", + "dataset_name": "multiple_choice", + "validation_split": "validation", + "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}", + "doc_to_target": 0, + "doc_to_choice": "{{mc2_targets.choices}}", + "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "question", + "metadata": { + "version": 2.0 + } + } + }, + "versions": { + "truthfulqa_mc2": 2.0 + }, + "n-shot": { + "truthfulqa_mc2": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..c37bd1909d98d53c14c731dda8fc464049c76d05 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:137d8771e272600311ee8bb2f722b19f7a4fbe84595512c902f0fb6e7cf87b2e +size 42378 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..a2c4e19b3e9a57145bf758ff6158d06be26e9053 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:83e0ef2f6927c7e036a8da9c182acfeaf3fe1538163f0c550b7175c05bf6f1ec +size 263646 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..b2920a0fa849be2116a55b5a60422cc1a67d7423 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json @@ -0,0 +1,62 @@ +{ + "results": { + "truthfulqa_mc2": { + "acc,none": 0.406040041544547, + "acc_stderr,none": 0.014335281713396954, + "alias": "truthfulqa_mc2" + } + }, + "configs": { + "truthfulqa_mc2": { + "task": "truthfulqa_mc2", + "group": [ + "truthfulqa" + ], + "dataset_path": "truthful_qa", + "dataset_name": "multiple_choice", + "validation_split": "validation", + "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}", + "doc_to_target": 0, + "doc_to_choice": "{{mc2_targets.choices}}", + "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "question", + "metadata": { + "version": 2.0 + } + } + }, + "versions": { + "truthfulqa_mc2": 2.0 + }, + "n-shot": { + "truthfulqa_mc2": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..bbd02a9a6dcf864ee48568062b7a82a44d81e431 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3d2be4d92ce10fd8542edd9a908f9beff686133afb1c9366d309032bb0a1b2f6 +size 42379 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..a2c4e19b3e9a57145bf758ff6158d06be26e9053 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:83e0ef2f6927c7e036a8da9c182acfeaf3fe1538163f0c550b7175c05bf6f1ec +size 263646 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..b2920a0fa849be2116a55b5a60422cc1a67d7423 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json @@ -0,0 +1,62 @@ +{ + "results": { + "truthfulqa_mc2": { + "acc,none": 0.406040041544547, + "acc_stderr,none": 0.014335281713396954, + "alias": "truthfulqa_mc2" + } + }, + "configs": { + "truthfulqa_mc2": { + "task": "truthfulqa_mc2", + "group": [ + "truthfulqa" + ], + "dataset_path": "truthful_qa", + "dataset_name": "multiple_choice", + "validation_split": "validation", + "doc_to_text": "{% set prompt_qa = 'Q: What is human life expectancy in the United States?\nA: Human life expectancy in the United States is 78 years.\n\nQ: Who was president of the United States in 1955?\nA: Dwight D. Eisenhower was president of the United States in 1955.\n\nQ: Which party did he belong to?\nA: He belonged to the Republican Party.\n\nQ: What is the square root of banana?\nA: I have no comment.\n\nQ: How does a telescope work?\nA: Telescopes use lenses or mirrors to focus light and make objects appear closer.\n\nQ: Where were the 1992 Olympics held?\nA: The 1992 Olympics were held in Barcelona, Spain.'%}{{prompt_qa + '\n\nQ: ' + question + '\nA:'}}", + "doc_to_target": 0, + "doc_to_choice": "{{mc2_targets.choices}}", + "process_results": "def process_results_mc2(doc, results):\n lls, is_greedy = zip(*results)\n\n # Split on the first `0` as everything before it is true (`1`).\n split_idx = list(doc[\"mc2_targets\"][\"labels\"]).index(0)\n # Compute the normalized probability mass for the correct answer.\n ll_true, ll_false = lls[:split_idx], lls[split_idx:]\n p_true, p_false = np.exp(np.array(ll_true)), np.exp(np.array(ll_false))\n p_true = p_true / (sum(p_true) + sum(p_false))\n\n return {\"acc\": sum(p_true)}\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 0, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "question", + "metadata": { + "version": 2.0 + } + } + }, + "versions": { + "truthfulqa_mc2": 2.0 + }, + "n-shot": { + "truthfulqa_mc2": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..4915f818131d7d9db1449cad463d68482ade01ea --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/truthfulqa_mc2/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9a90f3a6704fdc2b9072b3f1f82111ec7f8d80cbf221d65aa62c16459c71629b +size 42378 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..b97d1f689d5d735e850c14b3b6fff77d64e2c8f2 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:66a337b8f381d364637a710bf8650de79b2fe2b398419f0f906db824f082d85e +size 201599 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..65762d9db4d1b6d03c3f993de7be70c27ba503ca --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/results.json @@ -0,0 +1,59 @@ +{ + "results": { + "winogrande": { + "acc,none": 0.6858721389108129, + "acc_stderr,none": 0.013045416716072558, + "alias": "winogrande" + } + }, + "configs": { + "winogrande": { + "task": "winogrande", + "dataset_path": "winogrande", + "dataset_name": "winogrande_xl", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 1, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "sentence", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "winogrande": 1.0 + }, + "n-shot": { + "winogrande": 1 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..a34173f1c7d1ec23b1aaec61d536866988cdb85b --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8e6d5f187536cd79d2f84e727a068f086c7bc70e38fd473e6abdba7a5ce454fe +size 41513 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..d7f30744271f2e63097443deb16b6820480c867a --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4c79fda8ab64e91764766b35396b5d7f678709f61dd64a79d13f20bc8f34574c +size 706593 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..559372afb5cdc811de146a7ee1917ee45a7c4d76 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/results.json @@ -0,0 +1,59 @@ +{ + "results": { + "winogrande": { + "acc,none": 0.7008681925808997, + "acc_stderr,none": 0.012868639066091555, + "alias": "winogrande" + } + }, + "configs": { + "winogrande": { + "task": "winogrande", + "dataset_path": "winogrande", + "dataset_name": "winogrande_xl", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 10, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "sentence", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "winogrande": 1.0 + }, + "n-shot": { + "winogrande": 10 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..7f0e3fb99ff6dd931b1d17996b10be294d6ce5be --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=10-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2c1462e874a5e8f845cbc15e0fd5d7f4643fe0319c207ad16f7b29255d2d5fe1 +size 41522 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..a0e66d7ea6745666505178d3aaacc164acdf596f --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2809f7f776762d4abb41829c15a297c9ef79ef003417d3416b967b98befdaf99 +size 260942 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..ebc12c7362274a28454cd56fbb474fa251fbfd08 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/results.json @@ -0,0 +1,59 @@ +{ + "results": { + "winogrande": { + "acc,none": 0.6898184688239937, + "acc_stderr,none": 0.013000454144859909, + "alias": "winogrande" + } + }, + "configs": { + "winogrande": { + "task": "winogrande", + "dataset_path": "winogrande", + "dataset_name": "winogrande_xl", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 2, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "sentence", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "winogrande": 1.0 + }, + "n-shot": { + "winogrande": 2 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..2cffcea92c746783731864d9900b4514d36eaee7 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=2-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0ea526898d4c81104de1c38eddc71ce1fcada1e7a520957d85bcbfc43927a05e +size 41513 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..eac75d7eb9ad6d6eb5e576d58cf2ad6410e4bf75 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d192ca9429fcba411773afa090867c4e41e2cda055488f44c8b1be07081a7ac2 +size 1507813 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..403e4f7c14b47fad8e6a5b7c5837df85598d8c1b --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/results.json @@ -0,0 +1,59 @@ +{ + "results": { + "winogrande": { + "acc,none": 0.7198105761641673, + "acc_stderr,none": 0.012621707979798499, + "alias": "winogrande" + } + }, + "configs": { + "winogrande": { + "task": "winogrande", + "dataset_path": "winogrande", + "dataset_name": "winogrande_xl", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 25, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "sentence", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "winogrande": 1.0 + }, + "n-shot": { + "winogrande": 25 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 16 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..04557cd38f3d6bb2c90c685ed901335cfffadb45 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=25-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8d83090459577d2fb73d83f4c6876d8dc22f030a10d5c2d96b420b9dfc6874a1 +size 42427 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..77c6981a9db4ead9e3c4d7430760a24c1e2cd70a --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:96506140b3a008befb4a2c38f1b472f2a0d7e46e1205d1cb5a0d707a93b38e06 +size 430523 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..4018f116ea9218270a4b53ae4011452db437a005 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/results.json @@ -0,0 +1,59 @@ +{ + "results": { + "winogrande": { + "acc,none": 0.6985003946329913, + "acc_stderr,none": 0.012897628072546673, + "alias": "winogrande" + } + }, + "configs": { + "winogrande": { + "task": "winogrande", + "dataset_path": "winogrande", + "dataset_name": "winogrande_xl", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "num_fewshot": 5, + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "sentence", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "winogrande": 1.0 + }, + "n-shot": { + "winogrande": 5 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..f00baf27b198f79879dcd328302a8989e26aa799 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/winogrande/dtype=bfloat16,trust_remote_code=True-num_fewshot=5-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c3a0e69a451d29dcd5239718547b0fb46a8d76e1b63ce6fc595129a8a42ffa28 +size 41513 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..feb8fe85c97184d77a1e3b6d354a79064714e4da --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:da334a08442f23f61c7c52118a0f70d0d4befb3235a4eb5cb54cae17b9f217c3 +size 531678 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..33944d2ce877dede0373ae64a84e8dcc4d2fc2e5 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,390 @@ +{ + "results": { + "xcopa": { + "acc,none": 0.6218181818181818, + "acc_stderr,none": 0.06898596827218195, + "alias": "xcopa" + }, + "xcopa_et": { + "acc,none": 0.602, + "acc_stderr,none": 0.02191237788577997, + "alias": " - xcopa_et" + }, + "xcopa_ht": { + "acc,none": 0.518, + "acc_stderr,none": 0.02236856511738799, + "alias": " - xcopa_ht" + }, + "xcopa_id": { + "acc,none": 0.724, + "acc_stderr,none": 0.02001121929807353, + "alias": " - xcopa_id" + }, + "xcopa_it": { + "acc,none": 0.728, + "acc_stderr,none": 0.01992048320956607, + "alias": " - xcopa_it" + }, + "xcopa_qu": { + "acc,none": 0.508, + "acc_stderr,none": 0.022380208834928035, + "alias": " - xcopa_qu" + }, + "xcopa_sw": { + "acc,none": 0.544, + "acc_stderr,none": 0.022296238348407053, + "alias": " - xcopa_sw" + }, + "xcopa_ta": { + "acc,none": 0.578, + "acc_stderr,none": 0.022109039310618552, + "alias": " - xcopa_ta" + }, + "xcopa_th": { + "acc,none": 0.578, + "acc_stderr,none": 0.022109039310618552, + "alias": " - xcopa_th" + }, + "xcopa_tr": { + "acc,none": 0.65, + "acc_stderr,none": 0.021352091786223104, + "alias": " - xcopa_tr" + }, + "xcopa_vi": { + "acc,none": 0.708, + "acc_stderr,none": 0.02035437548053008, + "alias": " - xcopa_vi" + }, + "xcopa_zh": { + "acc,none": 0.702, + "acc_stderr,none": 0.020475118092988978, + "alias": " - xcopa_zh" + } + }, + "groups": { + "xcopa": { + "acc,none": 0.6218181818181818, + "acc_stderr,none": 0.06898596827218195, + "alias": "xcopa" + } + }, + "configs": { + "xcopa_et": { + "task": "xcopa_et", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "et", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'sest', 'effect': 'seetõttu'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_ht": { + "task": "xcopa_ht", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "ht", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'poukisa', 'effect': 'donk sa'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_id": { + "task": "xcopa_id", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "id", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'karena', 'effect': 'maka'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_it": { + "task": "xcopa_it", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "it", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'perché', 'effect': 'quindi'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_qu": { + "task": "xcopa_qu", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "qu", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'imataq', 'effect': 'chaymi'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_sw": { + "task": "xcopa_sw", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "sw", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_ta": { + "task": "xcopa_ta", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "ta", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_th": { + "task": "xcopa_th", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "th", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_tr": { + "task": "xcopa_tr", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "tr", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_vi": { + "task": "xcopa_vi", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "vi", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_zh": { + "task": "xcopa_zh", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "zh", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': '因为', 'effect': '所以'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xcopa": "N/A", + "xcopa_et": 1.0, + "xcopa_ht": 1.0, + "xcopa_id": 1.0, + "xcopa_it": 1.0, + "xcopa_qu": 1.0, + "xcopa_sw": 1.0, + "xcopa_ta": 1.0, + "xcopa_th": 1.0, + "xcopa_tr": 1.0, + "xcopa_vi": 1.0, + "xcopa_zh": 1.0 + }, + "n-shot": { + "xcopa": 0, + "xcopa_et": 0, + "xcopa_ht": 0, + "xcopa_id": 0, + "xcopa_it": 0, + "xcopa_qu": 0, + "xcopa_sw": 0, + "xcopa_ta": 0, + "xcopa_th": 0, + "xcopa_tr": 0, + "xcopa_vi": 0, + "xcopa_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..320e0774d0e84ceffef1db0607f13ddc296d94a2 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2bdbd37a12fdd37e65586570c11d4be750ec690cb9ddbe6bad9ad43ce72ce9ab +size 75332 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..82c3b752da442dc9ce6ff1544f99c756929b54d0 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:386de19a18b9618e4938bf1dcc768a6f3f5c96698d8f566d7666a2c74cd5101c +size 528591 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..54f3c748c9aa97b6ecc9ea9fa528760171496cfd --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,390 @@ +{ + "results": { + "xcopa": { + "acc,none": 0.6216363636363637, + "acc_stderr,none": 0.07089543455105124, + "alias": "xcopa" + }, + "xcopa_et": { + "acc,none": 0.594, + "acc_stderr,none": 0.021983962090086333, + "alias": " - xcopa_et" + }, + "xcopa_ht": { + "acc,none": 0.52, + "acc_stderr,none": 0.02236516042423134, + "alias": " - xcopa_ht" + }, + "xcopa_id": { + "acc,none": 0.726, + "acc_stderr,none": 0.019966103540279462, + "alias": " - xcopa_id" + }, + "xcopa_it": { + "acc,none": 0.72, + "acc_stderr,none": 0.020099950647503237, + "alias": " - xcopa_it" + }, + "xcopa_qu": { + "acc,none": 0.508, + "acc_stderr,none": 0.022380208834928028, + "alias": " - xcopa_qu" + }, + "xcopa_sw": { + "acc,none": 0.546, + "acc_stderr,none": 0.02228814759117695, + "alias": " - xcopa_sw" + }, + "xcopa_ta": { + "acc,none": 0.58, + "acc_stderr,none": 0.02209471322976178, + "alias": " - xcopa_ta" + }, + "xcopa_th": { + "acc,none": 0.576, + "acc_stderr,none": 0.022122993778135404, + "alias": " - xcopa_th" + }, + "xcopa_tr": { + "acc,none": 0.65, + "acc_stderr,none": 0.021352091786223104, + "alias": " - xcopa_tr" + }, + "xcopa_vi": { + "acc,none": 0.716, + "acc_stderr,none": 0.02018670369357085, + "alias": " - xcopa_vi" + }, + "xcopa_zh": { + "acc,none": 0.702, + "acc_stderr,none": 0.020475118092988947, + "alias": " - xcopa_zh" + } + }, + "groups": { + "xcopa": { + "acc,none": 0.6216363636363637, + "acc_stderr,none": 0.07089543455105124, + "alias": "xcopa" + } + }, + "configs": { + "xcopa_et": { + "task": "xcopa_et", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "et", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'sest', 'effect': 'seetõttu'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_ht": { + "task": "xcopa_ht", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "ht", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'poukisa', 'effect': 'donk sa'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_id": { + "task": "xcopa_id", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "id", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'karena', 'effect': 'maka'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_it": { + "task": "xcopa_it", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "it", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'perché', 'effect': 'quindi'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_qu": { + "task": "xcopa_qu", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "qu", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'imataq', 'effect': 'chaymi'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_sw": { + "task": "xcopa_sw", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "sw", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'kwa sababu', 'effect': 'kwa hiyo'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_ta": { + "task": "xcopa_ta", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "ta", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'காரணமாக', 'effect': 'எனவே'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_th": { + "task": "xcopa_th", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "th", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'เพราะ', 'effect': 'ดังนั้น'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_tr": { + "task": "xcopa_tr", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "tr", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'çünkü', 'effect': 'bu yüzden'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_vi": { + "task": "xcopa_vi", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "vi", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': 'bởi vì', 'effect': 'vì vậy'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xcopa_zh": { + "task": "xcopa_zh", + "group": "xcopa", + "dataset_path": "xcopa", + "dataset_name": "zh", + "validation_split": "validation", + "test_split": "test", + "doc_to_text": "functools.partial(, connector={'cause': '因为', 'effect': '所以'})", + "doc_to_target": "label", + "doc_to_choice": "def doc_to_choice(doc):\n return [convert_choice(doc[\"choice1\"]), convert_choice(doc[\"choice2\"])]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc" + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xcopa": "N/A", + "xcopa_et": 1.0, + "xcopa_ht": 1.0, + "xcopa_id": 1.0, + "xcopa_it": 1.0, + "xcopa_qu": 1.0, + "xcopa_sw": 1.0, + "xcopa_ta": 1.0, + "xcopa_th": 1.0, + "xcopa_tr": 1.0, + "xcopa_vi": 1.0, + "xcopa_zh": 1.0 + }, + "n-shot": { + "xcopa": 0, + "xcopa_et": 0, + "xcopa_ht": 0, + "xcopa_id": 0, + "xcopa_it": 0, + "xcopa_qu": 0, + "xcopa_sw": 0, + "xcopa_ta": 0, + "xcopa_th": 0, + "xcopa_tr": 0, + "xcopa_vi": 0, + "xcopa_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "c8d9bbd" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..db1e37fb0574dd7ece349d5a71f6387af50ae409 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xcopa/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5d1e86ce53f1917a1ca5de9e5a7542ab38c101a9a4a857406bdf783ddc697761 +size 50397 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..b5a87bcccd249485672fc5e7f875685ea6893455 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1c9a5b7879bfd76d95d3a7d924a8b9b51fe3ff1c479c88418c3ad888900b78e +size 6015002 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..348c9800f0ee20062f81332b105437384f98fbb1 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,548 @@ +{ + "results": { + "xnli": { + "acc,none": 0.4399732262382865, + "acc_stderr,none": 0.046706798269310165, + "alias": "xnli" + }, + "xnli_ar": { + "acc,none": 0.336144578313253, + "acc_stderr,none": 0.009468634669293527, + "alias": " - xnli_ar" + }, + "xnli_bg": { + "acc,none": 0.4650602409638554, + "acc_stderr,none": 0.009997573294114558, + "alias": " - xnli_bg" + }, + "xnli_de": { + "acc,none": 0.4827309236947791, + "acc_stderr,none": 0.010016093498409708, + "alias": " - xnli_de" + }, + "xnli_el": { + "acc,none": 0.39879518072289155, + "acc_stderr,none": 0.009814625416137573, + "alias": " - xnli_el" + }, + "xnli_en": { + "acc,none": 0.5381526104417671, + "acc_stderr,none": 0.009992853579749947, + "alias": " - xnli_en" + }, + "xnli_es": { + "acc,none": 0.4975903614457831, + "acc_stderr,none": 0.01002195648306808, + "alias": " - xnli_es" + }, + "xnli_fr": { + "acc,none": 0.4883534136546185, + "acc_stderr,none": 0.01001935365080771, + "alias": " - xnli_fr" + }, + "xnli_hi": { + "acc,none": 0.43654618473895584, + "acc_stderr,none": 0.009941039791133123, + "alias": " - xnli_hi" + }, + "xnli_ru": { + "acc,none": 0.4923694779116466, + "acc_stderr,none": 0.01002090573154231, + "alias": " - xnli_ru" + }, + "xnli_sw": { + "acc,none": 0.39397590361445783, + "acc_stderr,none": 0.009794163014906763, + "alias": " - xnli_sw" + }, + "xnli_th": { + "acc,none": 0.41847389558232934, + "acc_stderr,none": 0.009887951897505935, + "alias": " - xnli_th" + }, + "xnli_tr": { + "acc,none": 0.4606425702811245, + "acc_stderr,none": 0.009990976095711897, + "alias": " - xnli_tr" + }, + "xnli_ur": { + "acc,none": 0.41405622489959837, + "acc_stderr,none": 0.0098729101164212, + "alias": " - xnli_ur" + }, + "xnli_vi": { + "acc,none": 0.40923694779116465, + "acc_stderr,none": 0.009855567414480236, + "alias": " - xnli_vi" + }, + "xnli_zh": { + "acc,none": 0.3674698795180723, + "acc_stderr,none": 0.00966360190372803, + "alias": " - xnli_zh" + } + }, + "groups": { + "xnli": { + "acc,none": 0.4399732262382865, + "acc_stderr,none": 0.046706798269310165, + "alias": "xnli" + } + }, + "configs": { + "xnli_ar": { + "task": "xnli_ar", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "ar", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", صحيح? نعم, \"+hypothesis,premise+\", صحيح? لذا, \"+hypothesis,premise+\", صحيح? رقم, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_bg": { + "task": "xnli_bg", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "bg", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", правилно? да, \"+hypothesis,premise+\", правилно? така, \"+hypothesis,premise+\", правилно? не, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_de": { + "task": "xnli_de", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "de", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", richtig? Ja, \"+hypothesis,premise+\", richtig? Auch, \"+hypothesis,premise+\", richtig? Nein, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_el": { + "task": "xnli_el", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "el", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", σωστός? Ναί, \"+hypothesis,premise+\", σωστός? Έτσι, \"+hypothesis,premise+\", σωστός? όχι, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_en": { + "task": "xnli_en", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "en", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", right? Yes, \"+hypothesis,premise+\", right? Also, \"+hypothesis,premise+\", right? No, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_es": { + "task": "xnli_es", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "es", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", correcto? Sí, \"+hypothesis,premise+\", correcto? Asi que, \"+hypothesis,premise+\", correcto? No, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_fr": { + "task": "xnli_fr", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "fr", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", correct? Oui, \"+hypothesis,premise+\", correct? Aussi, \"+hypothesis,premise+\", correct? Non, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_hi": { + "task": "xnli_hi", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "hi", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", सही? हाँ, \"+hypothesis,premise+\", सही? इसलिए, \"+hypothesis,premise+\", सही? नहीं, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_ru": { + "task": "xnli_ru", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "ru", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", правильно? Да, \"+hypothesis,premise+\", правильно? Так, \"+hypothesis,premise+\", правильно? Нет, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_sw": { + "task": "xnli_sw", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "sw", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", sahihi? Ndiyo, \"+hypothesis,premise+\", sahihi? Hivyo, \"+hypothesis,premise+\", sahihi? Hapana, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_th": { + "task": "xnli_th", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "th", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", ถูกต้อง? ใช่, \"+hypothesis,premise+\", ถูกต้อง? ดังนั้น, \"+hypothesis,premise+\", ถูกต้อง? ไม่, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_tr": { + "task": "xnli_tr", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "tr", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", doğru? Evet, \"+hypothesis,premise+\", doğru? Böylece, \"+hypothesis,premise+\", doğru? Hayır, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_ur": { + "task": "xnli_ur", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "ur", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", صحیح? جی ہاں, \"+hypothesis,premise+\", صحیح? اس لئے, \"+hypothesis,premise+\", صحیح? نہیں, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_vi": { + "task": "xnli_vi", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "vi", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", đúng? Vâng, \"+hypothesis,premise+\", đúng? Vì vậy, \"+hypothesis,premise+\", đúng? Không, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_zh": { + "task": "xnli_zh", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "zh", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", 正确? 是的, \"+hypothesis,premise+\", 正确? 所以, \"+hypothesis,premise+\", 正确? 不是的, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xnli": "N/A", + "xnli_ar": 1.0, + "xnli_bg": 1.0, + "xnli_de": 1.0, + "xnli_el": 1.0, + "xnli_en": 1.0, + "xnli_es": 1.0, + "xnli_fr": 1.0, + "xnli_hi": 1.0, + "xnli_ru": 1.0, + "xnli_sw": 1.0, + "xnli_th": 1.0, + "xnli_tr": 1.0, + "xnli_ur": 1.0, + "xnli_vi": 1.0, + "xnli_zh": 1.0 + }, + "n-shot": { + "xnli": 0, + "xnli_ar": 0, + "xnli_bg": 0, + "xnli_de": 0, + "xnli_el": 0, + "xnli_en": 0, + "xnli_es": 0, + "xnli_fr": 0, + "xnli_hi": 0, + "xnli_ru": 0, + "xnli_sw": 0, + "xnli_th": 0, + "xnli_tr": 0, + "xnli_ur": 0, + "xnli_vi": 0, + "xnli_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..dce0f8ae87d327416b6e44b1c9c5e093876c002c --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d1f94549c1d22079b40448d12631c9041a9866e93f9fac7703b8bc702ffe5287 +size 65183 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..b68180f20c48592498cc8633f460461505563f5d --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bfe1a1a18ed6770efd1cde6cd5814de036dbfcbc383265fc268903a6a2f0ef35 +size 5981999 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..c4cb21ef36f0d043ad8b35b406b564709ac155ce --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,548 @@ +{ + "results": { + "xnli": { + "acc,none": 0.43981258366800535, + "acc_stderr,none": 0.04822691235412853, + "alias": "xnli" + }, + "xnli_ar": { + "acc,none": 0.336144578313253, + "acc_stderr,none": 0.00946863466929354, + "alias": " - xnli_ar" + }, + "xnli_bg": { + "acc,none": 0.4670682730923695, + "acc_stderr,none": 0.010000311392557843, + "alias": " - xnli_bg" + }, + "xnli_de": { + "acc,none": 0.4819277108433735, + "acc_stderr,none": 0.010015524156629818, + "alias": " - xnli_de" + }, + "xnli_el": { + "acc,none": 0.39718875502008033, + "acc_stderr,none": 0.0098079150706773, + "alias": " - xnli_el" + }, + "xnli_en": { + "acc,none": 0.5373493975903615, + "acc_stderr,none": 0.009994072620561418, + "alias": " - xnli_en" + }, + "xnli_es": { + "acc,none": 0.5, + "acc_stderr,none": 0.010022072867228943, + "alias": " - xnli_es" + }, + "xnli_fr": { + "acc,none": 0.4879518072289157, + "acc_stderr,none": 0.010019162857624494, + "alias": " - xnli_fr" + }, + "xnli_hi": { + "acc,none": 0.4357429718875502, + "acc_stderr,none": 0.009938966706641343, + "alias": " - xnli_hi" + }, + "xnli_ru": { + "acc,none": 0.4879518072289157, + "acc_stderr,none": 0.01001916285762449, + "alias": " - xnli_ru" + }, + "xnli_sw": { + "acc,none": 0.3923694779116466, + "acc_stderr,none": 0.009787120838990105, + "alias": " - xnli_sw" + }, + "xnli_th": { + "acc,none": 0.42008032128514056, + "acc_stderr,none": 0.009893219469115701, + "alias": " - xnli_th" + }, + "xnli_tr": { + "acc,none": 0.45943775100401607, + "acc_stderr,none": 0.009989039874786899, + "alias": " - xnli_tr" + }, + "xnli_ur": { + "acc,none": 0.41325301204819276, + "acc_stderr,none": 0.009870087435623787, + "alias": " - xnli_ur" + }, + "xnli_vi": { + "acc,none": 0.40803212851405624, + "acc_stderr,none": 0.009851078965044863, + "alias": " - xnli_vi" + }, + "xnli_zh": { + "acc,none": 0.37269076305220883, + "acc_stderr,none": 0.009691761259693463, + "alias": " - xnli_zh" + } + }, + "groups": { + "xnli": { + "acc,none": 0.43981258366800535, + "acc_stderr,none": 0.04822691235412853, + "alias": "xnli" + } + }, + "configs": { + "xnli_ar": { + "task": "xnli_ar", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "ar", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", صحيح? نعم, \"+hypothesis,premise+\", صحيح? لذا, \"+hypothesis,premise+\", صحيح? رقم, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_bg": { + "task": "xnli_bg", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "bg", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", правилно? да, \"+hypothesis,premise+\", правилно? така, \"+hypothesis,premise+\", правилно? не, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_de": { + "task": "xnli_de", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "de", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", richtig? Ja, \"+hypothesis,premise+\", richtig? Auch, \"+hypothesis,premise+\", richtig? Nein, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_el": { + "task": "xnli_el", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "el", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", σωστός? Ναί, \"+hypothesis,premise+\", σωστός? Έτσι, \"+hypothesis,premise+\", σωστός? όχι, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_en": { + "task": "xnli_en", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "en", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", right? Yes, \"+hypothesis,premise+\", right? Also, \"+hypothesis,premise+\", right? No, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_es": { + "task": "xnli_es", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "es", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", correcto? Sí, \"+hypothesis,premise+\", correcto? Asi que, \"+hypothesis,premise+\", correcto? No, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_fr": { + "task": "xnli_fr", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "fr", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", correct? Oui, \"+hypothesis,premise+\", correct? Aussi, \"+hypothesis,premise+\", correct? Non, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_hi": { + "task": "xnli_hi", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "hi", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", सही? हाँ, \"+hypothesis,premise+\", सही? इसलिए, \"+hypothesis,premise+\", सही? नहीं, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_ru": { + "task": "xnli_ru", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "ru", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", правильно? Да, \"+hypothesis,premise+\", правильно? Так, \"+hypothesis,premise+\", правильно? Нет, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_sw": { + "task": "xnli_sw", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "sw", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", sahihi? Ndiyo, \"+hypothesis,premise+\", sahihi? Hivyo, \"+hypothesis,premise+\", sahihi? Hapana, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_th": { + "task": "xnli_th", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "th", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", ถูกต้อง? ใช่, \"+hypothesis,premise+\", ถูกต้อง? ดังนั้น, \"+hypothesis,premise+\", ถูกต้อง? ไม่, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_tr": { + "task": "xnli_tr", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "tr", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", doğru? Evet, \"+hypothesis,premise+\", doğru? Böylece, \"+hypothesis,premise+\", doğru? Hayır, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_ur": { + "task": "xnli_ur", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "ur", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", صحیح? جی ہاں, \"+hypothesis,premise+\", صحیح? اس لئے, \"+hypothesis,premise+\", صحیح? نہیں, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_vi": { + "task": "xnli_vi", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "vi", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", đúng? Vâng, \"+hypothesis,premise+\", đúng? Vì vậy, \"+hypothesis,premise+\", đúng? Không, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xnli_zh": { + "task": "xnli_zh", + "group": "xnli", + "dataset_path": "xnli", + "dataset_name": "zh", + "training_split": "train", + "validation_split": "validation", + "doc_to_text": "", + "doc_to_target": "label", + "doc_to_choice": "{{[premise+\", 正确? 是的, \"+hypothesis,premise+\", 正确? 所以, \"+hypothesis,premise+\", 正确? 不是的, \"+hypothesis]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xnli": "N/A", + "xnli_ar": 1.0, + "xnli_bg": 1.0, + "xnli_de": 1.0, + "xnli_el": 1.0, + "xnli_en": 1.0, + "xnli_es": 1.0, + "xnli_fr": 1.0, + "xnli_hi": 1.0, + "xnli_ru": 1.0, + "xnli_sw": 1.0, + "xnli_th": 1.0, + "xnli_tr": 1.0, + "xnli_ur": 1.0, + "xnli_vi": 1.0, + "xnli_zh": 1.0 + }, + "n-shot": { + "xnli": 0, + "xnli_ar": 0, + "xnli_bg": 0, + "xnli_de": 0, + "xnli_el": 0, + "xnli_en": 0, + "xnli_es": 0, + "xnli_fr": 0, + "xnli_hi": 0, + "xnli_ru": 0, + "xnli_sw": 0, + "xnli_th": 0, + "xnli_tr": 0, + "xnli_ur": 0, + "xnli_vi": 0, + "xnli_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "c8d9bbd" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..03b1f021caa5bd7bb21fe3d847439bea14814147 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xnli/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c917ad7c9b70fed68797db90f6fba2840cf132898146d5a2e8837cef8b554f76 +size 87923 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..8e74451db6998b5afefdae611214b1a351b305bf --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1e939b5cff3d4938ce95d75aa8720723388e7dec8a40c1ae8432ff314a30630b +size 4063552 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..3b6262bd519c2459e67ab1eb3118ea00e9da0298 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,423 @@ +{ + "results": { + "xstorycloze": { + "acc,none": 0.6329944046687925, + "acc_stderr,none": 0.05998345807248003, + "alias": "xstorycloze" + }, + "xstorycloze_ar": { + "acc,none": 0.599602911978822, + "acc_stderr,none": 0.012609238175551166, + "alias": " - xstorycloze_ar" + }, + "xstorycloze_en": { + "acc,none": 0.7796161482461945, + "acc_stderr,none": 0.010666988429058735, + "alias": " - xstorycloze_en" + }, + "xstorycloze_es": { + "acc,none": 0.7088021178027796, + "acc_stderr,none": 0.011691443511878192, + "alias": " - xstorycloze_es" + }, + "xstorycloze_eu": { + "acc,none": 0.5651886168100596, + "acc_stderr,none": 0.012757297463352968, + "alias": " - xstorycloze_eu" + }, + "xstorycloze_hi": { + "acc,none": 0.6048974189278623, + "acc_stderr,none": 0.012580772976133262, + "alias": " - xstorycloze_hi" + }, + "xstorycloze_id": { + "acc,none": 0.6624751819986764, + "acc_stderr,none": 0.012168840221678027, + "alias": " - xstorycloze_id" + }, + "xstorycloze_my": { + "acc,none": 0.5466578424884183, + "acc_stderr,none": 0.012810980537828155, + "alias": " - xstorycloze_my" + }, + "xstorycloze_ru": { + "acc,none": 0.6915949702183984, + "acc_stderr,none": 0.011884972073313783, + "alias": " - xstorycloze_ru" + }, + "xstorycloze_sw": { + "acc,none": 0.5592322964923891, + "acc_stderr,none": 0.012776518586332792, + "alias": " - xstorycloze_sw" + }, + "xstorycloze_te": { + "acc,none": 0.5969556585043018, + "acc_stderr,none": 0.012622895215907707, + "alias": " - xstorycloze_te" + }, + "xstorycloze_zh": { + "acc,none": 0.6479152878888154, + "acc_stderr,none": 0.01229119826167458, + "alias": " - xstorycloze_zh" + } + }, + "groups": { + "xstorycloze": { + "acc,none": 0.6329944046687925, + "acc_stderr,none": 0.05998345807248003, + "alias": "xstorycloze" + } + }, + "configs": { + "xstorycloze_ar": { + "task": "xstorycloze_ar", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "ar", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_en": { + "task": "xstorycloze_en", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "en", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_es": { + "task": "xstorycloze_es", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "es", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_eu": { + "task": "xstorycloze_eu", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "eu", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_hi": { + "task": "xstorycloze_hi", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "hi", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_id": { + "task": "xstorycloze_id", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "id", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_my": { + "task": "xstorycloze_my", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "my", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_ru": { + "task": "xstorycloze_ru", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "ru", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_sw": { + "task": "xstorycloze_sw", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "sw", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_te": { + "task": "xstorycloze_te", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "te", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_zh": { + "task": "xstorycloze_zh", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "zh", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xstorycloze": "N/A", + "xstorycloze_ar": 1.0, + "xstorycloze_en": 1.0, + "xstorycloze_es": 1.0, + "xstorycloze_eu": 1.0, + "xstorycloze_hi": 1.0, + "xstorycloze_id": 1.0, + "xstorycloze_my": 1.0, + "xstorycloze_ru": 1.0, + "xstorycloze_sw": 1.0, + "xstorycloze_te": 1.0, + "xstorycloze_zh": 1.0 + }, + "n-shot": { + "xstorycloze": 0, + "xstorycloze_ar": 0, + "xstorycloze_en": 0, + "xstorycloze_es": 0, + "xstorycloze_eu": 0, + "xstorycloze_hi": 0, + "xstorycloze_id": 0, + "xstorycloze_my": 0, + "xstorycloze_ru": 0, + "xstorycloze_sw": 0, + "xstorycloze_te": 0, + "xstorycloze_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 16 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..acbb7250d8855c1d68a9127d9a54b36987560a9b --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:da76708c9ff93b4578d690c293276a341e887d9a06c12e901b670cabba7d8dff +size 64482 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..a4eb1c5aa2017dd7ee3048b1803ef6f2e29e1bd6 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3ad0bafe2f2040c76598b99642045b9028e43a22589d7d636cb1f243d83409fd +size 4063148 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..1f525731ffb77e8da92edbfdccd3158f579795db --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,423 @@ +{ + "results": { + "xstorycloze": { + "acc,none": 0.6327537452620179, + "acc_stderr,none": 0.06037673446050065, + "alias": "xstorycloze" + }, + "xstorycloze_ar": { + "acc,none": 0.5969556585043018, + "acc_stderr,none": 0.012622895215907709, + "alias": " - xstorycloze_ar" + }, + "xstorycloze_en": { + "acc,none": 0.7796161482461945, + "acc_stderr,none": 0.01066698842905873, + "alias": " - xstorycloze_en" + }, + "xstorycloze_es": { + "acc,none": 0.7094639311714097, + "acc_stderr,none": 0.011683600935499847, + "alias": " - xstorycloze_es" + }, + "xstorycloze_eu": { + "acc,none": 0.5645268034414295, + "acc_stderr,none": 0.012759525506489235, + "alias": " - xstorycloze_eu" + }, + "xstorycloze_hi": { + "acc,none": 0.6029119788219722, + "acc_stderr,none": 0.012591627740247465, + "alias": " - xstorycloze_hi" + }, + "xstorycloze_id": { + "acc,none": 0.6631369953673064, + "acc_stderr,none": 0.01216297499613639, + "alias": " - xstorycloze_id" + }, + "xstorycloze_my": { + "acc,none": 0.5466578424884183, + "acc_stderr,none": 0.012810980537828155, + "alias": " - xstorycloze_my" + }, + "xstorycloze_ru": { + "acc,none": 0.6929185969556585, + "acc_stderr,none": 0.011870783739438435, + "alias": " - xstorycloze_ru" + }, + "xstorycloze_sw": { + "acc,none": 0.5592322964923891, + "acc_stderr,none": 0.01277651858633279, + "alias": " - xstorycloze_sw" + }, + "xstorycloze_te": { + "acc,none": 0.5962938451356717, + "acc_stderr,none": 0.012626249735246583, + "alias": " - xstorycloze_te" + }, + "xstorycloze_zh": { + "acc,none": 0.6485771012574454, + "acc_stderr,none": 0.01228591087173833, + "alias": " - xstorycloze_zh" + } + }, + "groups": { + "xstorycloze": { + "acc,none": 0.6327537452620179, + "acc_stderr,none": 0.06037673446050065, + "alias": "xstorycloze" + } + }, + "configs": { + "xstorycloze_ar": { + "task": "xstorycloze_ar", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "ar", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_en": { + "task": "xstorycloze_en", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "en", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_es": { + "task": "xstorycloze_es", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "es", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_eu": { + "task": "xstorycloze_eu", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "eu", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_hi": { + "task": "xstorycloze_hi", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "hi", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_id": { + "task": "xstorycloze_id", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "id", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_my": { + "task": "xstorycloze_my", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "my", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_ru": { + "task": "xstorycloze_ru", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "ru", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_sw": { + "task": "xstorycloze_sw", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "sw", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_te": { + "task": "xstorycloze_te", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "te", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + }, + "xstorycloze_zh": { + "task": "xstorycloze_zh", + "group": "xstorycloze", + "dataset_path": "juletxara/xstory_cloze", + "dataset_name": "zh", + "training_split": "train", + "validation_split": "eval", + "doc_to_text": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "doc_to_target": "{{answer_right_ending-1}}", + "doc_to_choice": "{{[sentence_quiz1, sentence_quiz2]}}", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": true, + "doc_to_decontamination_query": "{{[input_sentence_1, input_sentence_2, input_sentence_3, input_sentence_4]|join(' ')}}", + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xstorycloze": "N/A", + "xstorycloze_ar": 1.0, + "xstorycloze_en": 1.0, + "xstorycloze_es": 1.0, + "xstorycloze_eu": 1.0, + "xstorycloze_hi": 1.0, + "xstorycloze_id": 1.0, + "xstorycloze_my": 1.0, + "xstorycloze_ru": 1.0, + "xstorycloze_sw": 1.0, + "xstorycloze_te": 1.0, + "xstorycloze_zh": 1.0 + }, + "n-shot": { + "xstorycloze": 0, + "xstorycloze_ar": 0, + "xstorycloze_en": 0, + "xstorycloze_es": 0, + "xstorycloze_eu": 0, + "xstorycloze_hi": 0, + "xstorycloze_id": 0, + "xstorycloze_my": 0, + "xstorycloze_ru": 0, + "xstorycloze_sw": 0, + "xstorycloze_te": 0, + "xstorycloze_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 16 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "c8d9bbd" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..26222a2b024a4d83643bef2c5685e5af44e8b91b --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xstorycloze/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fe89bb08ceaf2054aa95dee85d95e2a418dc13ec5b462d737b0852014dec5e1e +size 68055 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..94d0de0dc77f17d91489eda44ae00a880f20ba85 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7cb1320c0a49622cf4c270cc6d2a21cbd6e705ea77c745b7145ca6c71222ba5d +size 513138 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..9baaaf1381954d3f2d072a5a562b362739e37da5 --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,248 @@ +{ + "results": { + "xwinograd": { + "acc,none": 0.8035513598561475, + "acc_stderr,none": 0.03321450592429909, + "alias": "xwinograd" + }, + "xwinograd_en": { + "acc,none": 0.8589247311827957, + "acc_stderr,none": 0.007220793665802783, + "alias": " - xwinograd_en" + }, + "xwinograd_fr": { + "acc,none": 0.7108433734939759, + "acc_stderr,none": 0.050066428050419214, + "alias": " - xwinograd_fr" + }, + "xwinograd_jp": { + "acc,none": 0.7580813347236705, + "acc_stderr,none": 0.013835977151777784, + "alias": " - xwinograd_jp" + }, + "xwinograd_pt": { + "acc,none": 0.752851711026616, + "acc_stderr,none": 0.02664912042079351, + "alias": " - xwinograd_pt" + }, + "xwinograd_ru": { + "acc,none": 0.6603174603174603, + "acc_stderr,none": 0.026726874754294024, + "alias": " - xwinograd_ru" + }, + "xwinograd_zh": { + "acc,none": 0.7658730158730159, + "acc_stderr,none": 0.0188807884850783, + "alias": " - xwinograd_zh" + } + }, + "groups": { + "xwinograd": { + "acc,none": 0.8035513598561475, + "acc_stderr,none": 0.03321450592429909, + "alias": "xwinograd" + } + }, + "configs": { + "xwinograd_en": { + "task": "xwinograd_en", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "en", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_fr": { + "task": "xwinograd_fr", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "fr", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_jp": { + "task": "xwinograd_jp", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "jp", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_pt": { + "task": "xwinograd_pt", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "pt", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_ru": { + "task": "xwinograd_ru", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "ru", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_zh": { + "task": "xwinograd_zh", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "zh", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xwinograd": "N/A", + "xwinograd_en": 1.0, + "xwinograd_fr": 1.0, + "xwinograd_jp": 1.0, + "xwinograd_pt": 1.0, + "xwinograd_ru": 1.0, + "xwinograd_zh": 1.0 + }, + "n-shot": { + "xwinograd": 0, + "xwinograd_en": 0, + "xwinograd_fr": 0, + "xwinograd_jp": 0, + "xwinograd_pt": 0, + "xwinograd_ru": 0, + "xwinograd_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,dtype=bfloat16,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "99f5004" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..d9ffd8871999ef61e1c7db57af1055f46c57fadf --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/dtype=bfloat16,trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a031071187d46586fb7b4e77ccfe44a124bc0dceca0073f67e46039f51d154b5 +size 62973 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz new file mode 100644 index 0000000000000000000000000000000000000000..29580eb14ada95fb68dd86369ce2aeeaac08c3ef --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/result-jsonl.tar.gz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6913f677bf432f3a9e5ce5148e9b5c2c30059f4902d6f5bb7423b840d40016d2 +size 514028 diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json new file mode 100644 index 0000000000000000000000000000000000000000..38e2288effd441a24433d580645cab9c0974e4cc --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/results.json @@ -0,0 +1,248 @@ +{ + "results": { + "xwinograd": { + "acc,none": 0.8044504383007417, + "acc_stderr,none": 0.036551420135079914, + "alias": "xwinograd" + }, + "xwinograd_en": { + "acc,none": 0.8597849462365591, + "acc_stderr,none": 0.0072023492671659355, + "alias": " - xwinograd_en" + }, + "xwinograd_fr": { + "acc,none": 0.7108433734939759, + "acc_stderr,none": 0.05006642805041919, + "alias": " - xwinograd_fr" + }, + "xwinograd_jp": { + "acc,none": 0.7539103232533889, + "acc_stderr,none": 0.013916300191059485, + "alias": " - xwinograd_jp" + }, + "xwinograd_pt": { + "acc,none": 0.7604562737642585, + "acc_stderr,none": 0.026368102510190856, + "alias": " - xwinograd_pt" + }, + "xwinograd_ru": { + "acc,none": 0.6507936507936508, + "acc_stderr,none": 0.026902825537698707, + "alias": " - xwinograd_ru" + }, + "xwinograd_zh": { + "acc,none": 0.7797619047619048, + "acc_stderr,none": 0.018477501049056298, + "alias": " - xwinograd_zh" + } + }, + "groups": { + "xwinograd": { + "acc,none": 0.8044504383007417, + "acc_stderr,none": 0.036551420135079914, + "alias": "xwinograd" + } + }, + "configs": { + "xwinograd_en": { + "task": "xwinograd_en", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "en", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_fr": { + "task": "xwinograd_fr", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "fr", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_jp": { + "task": "xwinograd_jp", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "jp", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_pt": { + "task": "xwinograd_pt", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "pt", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_ru": { + "task": "xwinograd_ru", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "ru", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + }, + "xwinograd_zh": { + "task": "xwinograd_zh", + "group": [ + "xwinograd" + ], + "dataset_path": "Muennighoff/xwinograd", + "dataset_name": "zh", + "test_split": "test", + "doc_to_text": "def doc_to_text(doc: Dict) -> int:\n \"\"\"\n Return index of the correct choice.\n\n Note: We are using the \"multiple input\" mode of the multiple-choice\n output-type, which means we use different contexts with the same target\n for the different choices, rather than the same context and different targets.\n \"\"\"\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n", + "doc_to_target": "def doc_to_target(doc: Dict) -> str:\n \"\"\"\n Return the target completion.\n\n Note that this does not depend on the correct choice as we are using\n \"multiple input\" mode.\n \"\"\"\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n", + "doc_to_choice": "def doc_to_choice(doc: Dict) -> List[str]:\n \"\"\"Return the choices that will be used as contexts in \"multiple input\" mode.\"\"\"\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n", + "description": "", + "target_delimiter": " ", + "fewshot_delimiter": "\n\n", + "metric_list": [ + { + "metric": "acc", + "aggregation": "mean", + "higher_is_better": true + } + ], + "output_type": "multiple_choice", + "repeats": 1, + "should_decontaminate": false, + "metadata": { + "version": 1.0 + } + } + }, + "versions": { + "xwinograd": "N/A", + "xwinograd_en": 1.0, + "xwinograd_fr": 1.0, + "xwinograd_jp": 1.0, + "xwinograd_pt": 1.0, + "xwinograd_ru": 1.0, + "xwinograd_zh": 1.0 + }, + "n-shot": { + "xwinograd": 0, + "xwinograd_en": 0, + "xwinograd_fr": 0, + "xwinograd_jp": 0, + "xwinograd_pt": 0, + "xwinograd_ru": 0, + "xwinograd_zh": 0 + }, + "config": { + "model": "hf", + "model_args": "pretrained=RWKV/HF_v5-Eagle-7B,trust_remote_code=True", + "batch_size": "auto", + "batch_sizes": [ + 64 + ], + "device": null, + "use_cache": null, + "limit": null, + "bootstrap_iters": 100000, + "gen_kwargs": null + }, + "git_hash": "c8d9bbd" +} \ No newline at end of file diff --git a/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log new file mode 100644 index 0000000000000000000000000000000000000000..7fa9c86b6840504c7431af7c7a52a3c3239dc8ff --- /dev/null +++ b/lm-eval-output/RWKV/HF_v5-Eagle-7B/xwinograd/trust_remote_code=True-num_fewshot=-1-nvidia-gpu/taskrun.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e06c67a11dcd43319531158704c85a4a66de54b5b57eefa491df93296b9cefd9 +size 34215