| --- |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: GPT2-705M |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # GPT2-705M |
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| This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 3.3542 |
|
|
| ## Model description |
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| More information needed |
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| ## Intended uses & limitations |
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| More information needed |
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| ## Training and evaluation data |
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| More information needed |
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| ## Training procedure |
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| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 0.00025 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 50 |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
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|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 6.7388 | 1.0 | 3 | 6.6745 | |
| | 7.7712 | 2.0 | 6 | 6.9355 | |
| | 5.7851 | 3.0 | 9 | 6.0090 | |
| | 4.8315 | 4.0 | 12 | 5.7252 | |
| | 4.7133 | 5.0 | 15 | 5.2462 | |
| | 4.7276 | 6.0 | 18 | 4.9371 | |
| | 4.2828 | 7.0 | 21 | 4.8806 | |
| | 4.3069 | 8.0 | 24 | 4.4319 | |
| | 4.1875 | 9.0 | 27 | 4.2952 | |
| | 3.8318 | 10.0 | 30 | 4.1134 | |
| | 3.6746 | 11.0 | 33 | 3.9505 | |
| | 3.5241 | 12.0 | 36 | 3.7828 | |
| | 3.2439 | 13.0 | 39 | 3.7290 | |
| | 3.2954 | 14.0 | 42 | 3.5655 | |
| | 2.9475 | 15.0 | 45 | 3.4805 | |
| | 2.9343 | 16.0 | 48 | 3.5263 | |
| | 2.8517 | 17.0 | 51 | 3.4318 | |
| | 2.5458 | 18.0 | 54 | 3.3942 | |
| | 2.4846 | 19.0 | 57 | 3.3714 | |
| | 2.5766 | 20.0 | 60 | 3.3542 | |
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| ### Framework versions |
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| - Transformers 4.39.1 |
| - Pytorch 2.1.2+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
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|
