| --- |
| 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: 5.4628 |
|
|
| ## 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 |
|
|
| ### 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: 40 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
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|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 9.7135 | 0.57 | 1 | 9.7272 | |
| | 8.0222 | 1.71 | 3 | 9.3213 | |
| | 7.6063 | 2.86 | 5 | 8.5841 | |
| | 7.5596 | 4.0 | 7 | 7.9271 | |
| | 7.4194 | 4.57 | 8 | 8.0942 | |
| | 7.1644 | 5.71 | 10 | 7.5409 | |
| | 6.8531 | 6.86 | 12 | 7.3028 | |
| | 6.3614 | 8.0 | 14 | 9.3796 | |
| | 8.5129 | 8.57 | 15 | 7.6361 | |
| | 6.1325 | 9.71 | 17 | 6.7577 | |
| | 5.8526 | 10.86 | 19 | 6.5249 | |
| | 5.5941 | 12.0 | 21 | 6.2490 | |
| | 5.4307 | 12.57 | 22 | 6.2442 | |
| | 5.1381 | 13.71 | 24 | 5.9595 | |
| | 4.8705 | 14.86 | 26 | 5.8944 | |
| | 4.7083 | 16.0 | 28 | 5.7005 | |
| | 4.5355 | 16.57 | 29 | 5.7459 | |
| | 4.4187 | 17.71 | 31 | 5.5387 | |
| | 4.3123 | 18.86 | 33 | 5.4863 | |
| | 4.0269 | 20.0 | 35 | 5.3277 | |
| | 3.942 | 20.57 | 36 | 5.3274 | |
| | 3.784 | 21.71 | 38 | 5.3998 | |
| | 3.4991 | 22.86 | 40 | 5.4628 | |
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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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|
