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--- |
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license: mit |
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base_model: Aravindan/gpt2out |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: gpt2coder-8epochs |
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results: [] |
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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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# gpt2coder-8epochs |
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This model is a fine-tuned version of [Aravindan/gpt2out](https://huggingface.co/Aravindan/gpt2out) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9270 |
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## 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: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 10 |
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- total_train_batch_size: 80 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| No log | 0.9810 | 31 | 3.2508 | |
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| No log | 1.9937 | 63 | 2.6920 | |
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| No log | 2.9747 | 94 | 2.3769 | |
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| No log | 3.9873 | 126 | 2.1444 | |
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| No log | 5.0 | 158 | 1.9673 | |
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| No log | 5.9810 | 189 | 1.8320 | |
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| No log | 6.9937 | 221 | 1.7097 | |
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| No log | 7.9747 | 252 | 1.6159 | |
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| No log | 8.9873 | 284 | 1.5231 | |
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| No log | 10.0 | 316 | 1.4535 | |
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| No log | 10.9810 | 347 | 1.3788 | |
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| No log | 11.9937 | 379 | 1.3109 | |
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| No log | 12.9747 | 410 | 1.2496 | |
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| No log | 13.9873 | 442 | 1.1989 | |
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| No log | 14.9810 | 465 | 1.1647 | |
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| No log | 15.9937 | 497 | 1.1208 | |
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| 1.3856 | 16.9747 | 528 | 1.0841 | |
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| 1.3856 | 17.9873 | 560 | 1.0464 | |
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| 1.3856 | 19.0 | 592 | 1.0180 | |
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| 1.3856 | 19.9810 | 623 | 0.9928 | |
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| 1.3856 | 20.9937 | 655 | 0.9689 | |
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| 1.3856 | 21.9747 | 686 | 0.9517 | |
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| 1.3856 | 22.9873 | 718 | 0.9390 | |
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| 1.3856 | 24.0 | 750 | 0.9298 | |
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| 1.3856 | 24.7911 | 775 | 0.9270 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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