| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: distilgpt2 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: results |
| | 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. --> |
| |
|
| | # results |
| |
|
| | This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4903 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 8 |
| | - 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: linear |
| | - lr_scheduler_warmup_steps: 200 |
| | - num_epochs: 3 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:------:|:-----:|:---------------:| |
| | | 3.487 | 0.1216 | 500 | 2.7628 | |
| | | 2.4975 | 0.2433 | 1000 | 2.2091 | |
| | | 2.2501 | 0.3649 | 1500 | 1.8555 | |
| | | 2.0317 | 0.4866 | 2000 | 1.6036 | |
| | | 1.951 | 0.6082 | 2500 | 1.4196 | |
| | | 1.8645 | 0.7298 | 3000 | 1.2600 | |
| | | 1.7716 | 0.8515 | 3500 | 1.1290 | |
| | | 1.7462 | 0.9731 | 4000 | 1.0334 | |
| | | 1.6157 | 1.0946 | 4500 | 0.9300 | |
| | | 1.5509 | 1.2163 | 5000 | 0.8553 | |
| | | 1.5186 | 1.3379 | 5500 | 0.7855 | |
| | | 1.4767 | 1.4596 | 6000 | 0.7299 | |
| | | 1.4667 | 1.5812 | 6500 | 0.6972 | |
| | | 1.481 | 1.7028 | 7000 | 0.6611 | |
| | | 1.4245 | 1.8245 | 7500 | 0.6109 | |
| | | 1.4017 | 1.9461 | 8000 | 0.5911 | |
| | | 1.3376 | 2.0676 | 8500 | 0.5671 | |
| | | 1.3276 | 2.1893 | 9000 | 0.5600 | |
| | | 1.3228 | 2.3109 | 9500 | 0.5398 | |
| | | 1.3184 | 2.4326 | 10000 | 0.5246 | |
| | | 1.2939 | 2.5542 | 10500 | 0.5100 | |
| | | 1.3121 | 2.6758 | 11000 | 0.5025 | |
| | | 1.2904 | 2.7975 | 11500 | 0.4938 | |
| | | 1.2743 | 2.9191 | 12000 | 0.4903 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.56.1 |
| | - Pytorch 2.8.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.0 |
| | |
