| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: gpt2_small |
| | 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. --> |
| |
|
| | # gpt2_small |
| | |
| | This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 4.0095 |
| | - Accuracy: 0.8 |
| | - Precision: 0.25 |
| | - Recall: 0.0882 |
| | - F1: 0.1304 |
| | - D-index: 1.4492 |
| | |
| | ## 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: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 1600 |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | D-index | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| |
| | | No log | 1.0 | 200 | 1.4996 | 0.79 | 0.1667 | 0.0588 | 0.0870 | 1.4242 | |
| | | No log | 2.0 | 400 | 0.6186 | 0.79 | 0.2143 | 0.0882 | 0.125 | 1.4354 | |
| | | 2.445 | 3.0 | 600 | 0.8246 | 0.825 | 0.0 | 0.0 | 0.0 | 1.4500 | |
| | | 2.445 | 4.0 | 800 | 0.5725 | 0.81 | 0.0 | 0.0 | 0.0 | 1.4293 | |
| | | 0.6727 | 5.0 | 1000 | 1.1303 | 0.82 | 0.25 | 0.0294 | 0.0526 | 1.4543 | |
| | | 0.6727 | 6.0 | 1200 | 1.3270 | 0.82 | 0.3333 | 0.0588 | 0.1 | 1.4655 | |
| | | 0.6727 | 7.0 | 1400 | 2.4838 | 0.82 | 0.0 | 0.0 | 0.0 | 1.4431 | |
| | | 0.2813 | 8.0 | 1600 | 2.2778 | 0.79 | 0.2143 | 0.0882 | 0.125 | 1.4354 | |
| | | 0.2813 | 9.0 | 1800 | 2.8120 | 0.82 | 0.25 | 0.0294 | 0.0526 | 1.4543 | |
| | | 0.1174 | 10.0 | 2000 | 2.6462 | 0.795 | 0.1818 | 0.0588 | 0.0889 | 1.4312 | |
| | | 0.1174 | 11.0 | 2200 | 3.1627 | 0.795 | 0.2308 | 0.0882 | 0.1277 | 1.4423 | |
| | | 0.1174 | 12.0 | 2400 | 3.3766 | 0.795 | 0.2308 | 0.0882 | 0.1277 | 1.4423 | |
| | | 0.0319 | 13.0 | 2600 | 3.6674 | 0.8 | 0.2857 | 0.1176 | 0.1667 | 1.4603 | |
| | | 0.0319 | 14.0 | 2800 | 3.4900 | 0.78 | 0.1875 | 0.0882 | 0.12 | 1.4216 | |
| | | 0.0136 | 15.0 | 3000 | 3.7351 | 0.795 | 0.1818 | 0.0588 | 0.0889 | 1.4312 | |
| | | 0.0136 | 16.0 | 3200 | 3.8282 | 0.8 | 0.25 | 0.0882 | 0.1304 | 1.4492 | |
| | | 0.0136 | 17.0 | 3400 | 3.9465 | 0.8 | 0.25 | 0.0882 | 0.1304 | 1.4492 | |
| | | 0.0002 | 18.0 | 3600 | 4.0329 | 0.8 | 0.25 | 0.0882 | 0.1304 | 1.4492 | |
| | | 0.0002 | 19.0 | 3800 | 3.9581 | 0.795 | 0.2308 | 0.0882 | 0.1277 | 1.4423 | |
| | | 0.0015 | 20.0 | 4000 | 4.0095 | 0.8 | 0.25 | 0.0882 | 0.1304 | 1.4492 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| |
|
