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End of training

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  1. .gitattributes +1 -0
  2. README.md +156 -0
  3. benchmarks.shelve.bak +2 -0
  4. benchmarks.shelve.dat +3 -0
  5. benchmarks.shelve.dir +2 -0
  6. config.json +39 -0
  7. generation_config.json +6 -0
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  41. merges.txt +0 -0
  42. model.safetensors +3 -0
  43. special_tokens_map.json +6 -0
  44. tokenizer.json +0 -0
  45. tokenizer_config.json +20 -0
  46. training_args.bin +3 -0
  47. vocab.json +0 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ benchmarks.shelve.dat filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ base_model: gpt2
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+ datasets:
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+ - wikimedia/wikipedia
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+ library_name: Distily
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+ license: mit
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+ tags:
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+ - bitnet
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+ - 1.58b
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+ - generated_from_trainer
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+ model-index:
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+ - name: distily_test_attn_miles
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+ results: []
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+ ---
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+
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+
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+ # Summary
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+
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+ Distilled with [Distily](https://github.com/lapp0/distily) library
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+ using teacher model [gpt2](https://huggingface.co/gpt2)
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+ on dataset [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia).
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment.
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+
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+ # Model description
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+
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+ More information needed
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+
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+ # Intended uses & limitations
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+
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+ More information needed
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+ -->
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+
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+ # Model Architecture:
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+ - **Architecture**: `GPT2LMHeadModel`
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+ - **Total Parameters**: 124,439,808
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+ - **Data Type (dtype)**: torch.bfloat16
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+ - **Model Size**: 0.24 GB
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+
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+
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+ # Benchmark Metrics Comparison
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+
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+ | Metric | attn_layer_mapper=all, attn_loss_fn=raw_mse, attn_projector=miles | teacher |
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+ | :--- | :--- | :--- |
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+ | ai2_arc (acc) | 0.256 | 0.304 |
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+ | ai2_arc (acc_norm) | 0.267 | 0.309 |
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+ | arc_challenge (acc) | 0.177 | 0.184 |
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+ | arc_challenge (acc_norm) | 0.202 | 0.214 |
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+ | arc_easy (acc) | 0.335 | 0.424 |
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+ | arc_easy (acc_norm) | 0.332 | 0.405 |
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+ | boolq (acc) | 0.377 | 0.541 |
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+ | cola (mcc) | 0.0 | 0.009 |
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+ | glue (acc) | 0.444 | 0.41 |
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+ | glue (f1) | 0.279 | 0.526 |
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+ | glue (mcc) | 0.0 | 0.009 |
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+ | hellaswag (acc) | 0.302 | 0.337 |
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+ | hellaswag (acc_norm) | 0.308 | 0.384 |
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+ | mnli (acc) | 0.331 | 0.323 |
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+ | mnli_mismatch (acc) | 0.367 | 0.344 |
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+ | mrpc (acc) | 0.336 | 0.515 |
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+ | mrpc (f1) | 0.075 | 0.631 |
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+ | qnli (acc) | 0.519 | 0.472 |
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+ | qqp (acc) | 0.515 | 0.34 |
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+ | qqp (f1) | 0.363 | 0.483 |
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+ | rte (acc) | 0.57 | 0.516 |
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+ | sst2 (acc) | 0.498 | 0.511 |
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+ | wikitext (bits_per_byte) | 1.273 | 0.98 |
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+ | wikitext (byte_perplexity) | 2.416 | 1.973 |
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+ | wikitext (word_perplexity) | 111.9 | 37.82 |
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+ | wnli (acc) | 0.521 | 0.451 |
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+
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+ # Resource Usage Comparison
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+
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+ - VRAM Use: 7.7854 GB
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+
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+ # Distillation (Teacher -> Student) Architecture Difference:
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+
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+ - **Architecture**: `GPT2LMHeadModel` -> `GPT2LMHeadModel`
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+ - **Total Parameters**: 124,439,808 -> 124,439,808
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+ - **Data Type (dtype)**: torch.bfloat16 -> torch.bfloat16
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+ - **Model Size**: 0.24 GB -> 0.24 GB
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+
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+ <details>
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+ <summary>Module Diff Details</summary>
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+
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+ ```diff
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+
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+ ```
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+
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+ </details>
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+ <br/>
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+
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+ # Train Dataset
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+ Trained on 145,722,156 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
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+
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+ - Num Samples: `247,500`
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+ - Subset: `20231101.en`
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+ - Split: `train`
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+
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+
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+ # Training Objective
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+
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+ ```
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+ DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=25.0, loss_fn=raw_mse, layer_mapper=all, projector=miles))
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+ ```
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+
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+ # Hyperparameters
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+ The following hyperparameters were used during training:
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+
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+ <details>
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+ <summary>Expand</summary>
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+
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+ - learning_rate: `0.0001`
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+ - train_batch_size: `4`
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+ - eval_batch_size: `8`
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+ - seed: `42`
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+ - optimizer: `Adam with betas=(0.9,0.999) and epsilon=1e-08`
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+ - lr_scheduler_type: `cosine_with_min_lr`
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+ - lr_scheduler_warmup_ratio: `0.5`
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+ - num_epochs: `1.0`
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+ - distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=25.0, loss_fn=raw_mse, layer_mapper=all, projector=miles))`
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+ - train_embeddings: `True`
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+ - lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f6efc464fd0>`
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+ - student_model_name_or_path: `None`
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+ - student_config_name_or_path: `None`
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+ - student_model_config: `None`
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+ - reinitialize_weights: `None`
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+ - copy_teacher_modules: `[('lm_head', False)]`
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+ - student_model_as_bitnet: `True`
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+ - dropout: `None`
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+ - teacher_model_name_or_path: `gpt2`
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+ - teacher_load_in_8bit: `False`
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+ - teacher_load_in_4bit: `False`
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+ - dataset_uri: `wikimedia/wikipedia`
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+ - dataset_subset: `20231101.en`
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+ - dataset_split: `train`
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+ - dataset_column_name: `text`
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+ - dataset_sample_size: `250000`
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+ - dataset_test_size: `0.01`
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+ - gradient_accumulation_steps: `1`
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+ - weight_decay: `0.0`
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+ - max_grad_norm: `1.0`
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+ - warmup_ratio: `0.5`
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+ - warmup_steps: `0`
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+ - gradient_checkpointing: `True`
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+
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+ </details>
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+ <br/>
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+
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+
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+ # Framework Versions
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+ - Distily 0.3.0
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+ - Transformers 4.44.0
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+ - Pytorch 2.3.0
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+ - Datasets 2.21.0
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