| --- |
| library_name: transformers |
| license: mit |
| base_model: gpt2 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: codeparrot-ds |
| 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. --> |
|
|
| # codeparrot-ds |
|
|
| 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: 1.0537 |
|
|
| ## 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 |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:-----:|:---------------:| |
| | 2.5508 | 0.0766 | 5000 | 1.7315 | |
| | 1.6691 | 0.1533 | 10000 | 1.5102 | |
| | 1.5237 | 0.2299 | 15000 | 1.4152 | |
| | 1.4431 | 0.3065 | 20000 | 1.3476 | |
| | 1.3836 | 0.3832 | 25000 | 1.2948 | |
| | 1.3352 | 0.4598 | 30000 | 1.2483 | |
| | 1.2887 | 0.5365 | 35000 | 1.2047 | |
| | 1.2419 | 0.6131 | 40000 | 1.1618 | |
| | 1.2014 | 0.6897 | 45000 | 1.1249 | |
| | 1.164 | 0.7664 | 50000 | 1.0920 | |
| | 1.1363 | 0.8430 | 55000 | 1.0685 | |
| | 1.1165 | 0.9196 | 60000 | 1.0564 | |
| | 1.108 | 0.9963 | 65000 | 1.0537 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.6 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
