| --- |
| library_name: transformers |
| license: mit |
| base_model: gpt2 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - code_search_net |
| model-index: |
| - name: python_codeparrot |
| 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_codeparrot |
| |
| This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the code_search_net dataset. |
| |
| ## 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: 1 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
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|
| ### Framework versions |
|
|
| - Transformers 4.55.4 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.4 |
|
|
