| --- |
| library_name: transformers |
| license: mit |
| base_model: openai-community/gpt2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: clm-gpt2 |
| 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. --> |
|
|
| # clm-gpt2 |
|
|
| This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5054 |
| - Accuracy: 0.6325 |
|
|
| ## 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: 0.003 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 3.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:-----:|:---------------:|:--------:| |
| | 2.4536 | 0.1302 | 500 | 2.1316 | 0.4955 | |
| | 2.1054 | 0.2603 | 1000 | 2.0124 | 0.5221 | |
| | 1.9756 | 0.3905 | 1500 | 1.9025 | 0.5453 | |
| | 1.8863 | 0.5206 | 2000 | 1.8367 | 0.5601 | |
| | 1.8283 | 0.6508 | 2500 | 1.7927 | 0.5686 | |
| | 1.7893 | 0.7809 | 3000 | 1.7585 | 0.5760 | |
| | 1.7555 | 0.9111 | 3500 | 1.7328 | 0.5815 | |
| | 1.7143 | 1.0413 | 4000 | 1.7016 | 0.5882 | |
| | 1.6697 | 1.1714 | 4500 | 1.6813 | 0.5930 | |
| | 1.6584 | 1.3016 | 5000 | 1.6615 | 0.5972 | |
| | 1.6438 | 1.4317 | 5500 | 1.6422 | 0.6009 | |
| | 1.6184 | 1.5619 | 6000 | 1.6236 | 0.6049 | |
| | 1.6086 | 1.6920 | 6500 | 1.6102 | 0.6082 | |
| | 1.5882 | 1.8222 | 7000 | 1.5938 | 0.6114 | |
| | 1.5719 | 1.9524 | 7500 | 1.5786 | 0.6148 | |
| | 1.5272 | 2.0825 | 8000 | 1.5718 | 0.6175 | |
| | 1.4971 | 2.2127 | 8500 | 1.5593 | 0.6204 | |
| | 1.4893 | 2.3428 | 9000 | 1.5475 | 0.6227 | |
| | 1.4808 | 2.4730 | 9500 | 1.5382 | 0.6251 | |
| | 1.4689 | 2.6031 | 10000 | 1.5274 | 0.6275 | |
| | 1.4572 | 2.7333 | 10500 | 1.5169 | 0.6298 | |
| | 1.4488 | 2.8635 | 11000 | 1.5106 | 0.6315 | |
| | 1.4465 | 2.9936 | 11500 | 1.5054 | 0.6325 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
