| --- |
| library_name: transformers |
| license: mit |
| base_model: gpt2 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: python-code-model |
| 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. --> |
|
|
| # python-code-model |
|
|
| This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.8969 |
|
|
| ## 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: 0.0005 |
| - train_batch_size: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 256 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 3 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 5.3936 | 0.4827 | 500 | 3.6571 | |
| | 3.1064 | 0.9654 | 1000 | 2.7322 | |
| | 2.4375 | 1.4479 | 1500 | 2.3305 | |
| | 2.1386 | 1.9306 | 2000 | 2.0923 | |
| | 1.8331 | 2.4132 | 2500 | 1.9542 | |
| | 1.7149 | 2.8959 | 3000 | 1.8969 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
