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.ipynb_checkpoints/README-checkpoint.md

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+---
+license: bigcode-openrail-m
+base_model: bigcode/starcoderbase
+tags:
+- generated_from_trainer
+datasets:
+- fals3/methods2test_small
+metrics:
+- accuracy
+model-index:
+- name: output
+  results:
+  - task:
+      name: Causal Language Modeling
+      type: text-generation
+    dataset:
+      name: fals3/methods2test_small fm+fc+c+m+f+t+tc
+      type: fals3/methods2test_small
+      args: fm+fc+c+m+f+t+tc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5611769226558302
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# output
+
+This model is a fine-tuned version of [bigcode/starcoderbase](https://huggingface.co/bigcode/starcoderbase) on the fals3/methods2test_small fm+fc+c+m+f+t+tc dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6457
+- Accuracy: 0.5612
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 6
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 48
+- total_eval_batch_size: 6
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.41.0.dev0
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.1
+- Tokenizers 0.19.1

README.md

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+---
+license: bigcode-openrail-m
+base_model: bigcode/starcoderbase
+tags:
+- generated_from_trainer
+datasets:
+- fals3/methods2test_small
+metrics:
+- accuracy
+model-index:
+- name: output
+  results:
+  - task:
+      name: Causal Language Modeling
+      type: text-generation
+    dataset:
+      name: fals3/methods2test_small fm+fc+c+m+f+t+tc
+      type: fals3/methods2test_small
+      args: fm+fc+c+m+f+t+tc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5611769226558302
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# output
+
+This model is a fine-tuned version of [bigcode/starcoderbase](https://huggingface.co/bigcode/starcoderbase) on the fals3/methods2test_small fm+fc+c+m+f+t+tc dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6457
+- Accuracy: 0.5612
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 6
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 48
+- total_eval_batch_size: 6
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.41.0.dev0
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.1
+- Tokenizers 0.19.1

all_results.json

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+{
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+    "eval_accuracy": 0.5611769226558302,
+    "eval_loss": 0.6457484364509583,
+    "eval_runtime": 38.6111,
+    "eval_samples": 931,
+    "eval_samples_per_second": 24.112,
+    "eval_steps_per_second": 4.04,
+    "perplexity": 1.9074140733989902,
+    "total_flos": 9.99505283128492e+17,
+    "train_loss": 0.5814478738155323,
+    "train_runtime": 61267.4818,
+    "train_samples": 7283,
+    "train_samples_per_second": 0.357,
+    "train_steps_per_second": 0.007
+}

config.json

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+  "activation_function": "gelu",
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+    "GPTBigCodeForCausalLM"
+  ],
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+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.0.dev0",
+  "use_cache": true,
+  "validate_runner_input": true,
+  "vocab_size": 49152
+}

eval_results.json

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+    "eval_accuracy": 0.5611769226558302,
+    "eval_loss": 0.6457484364509583,
+    "eval_runtime": 38.6111,
+    "eval_samples": 931,
+    "eval_samples_per_second": 24.112,
+    "eval_steps_per_second": 4.04,
+    "perplexity": 1.9074140733989902
+}

generation_config.json

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+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "4.41.0.dev0"
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