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gpt2_sm_cv_summarized_4
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4906
- Accuracy: 0.743
- Precision: 0.3038
- Recall: 0.2462
- F1: 0.2720
- D-index: 1.4383
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 8000
- 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 | 250 | 1.0827 | 0.673 | 0.2155 | 0.2564 | 0.2342 | 1.3419 |
| 2.5863 | 2.0 | 500 | 0.6038 | 0.761 | 0.2381 | 0.1026 | 0.1434 | 1.4124 |
| 2.5863 | 3.0 | 750 | 0.5238 | 0.794 | 0.3333 | 0.0564 | 0.0965 | 1.4421 |
| 0.5205 | 4.0 | 1000 | 0.5206 | 0.798 | 0.3158 | 0.0308 | 0.0561 | 1.4384 |
| 0.5205 | 5.0 | 1250 | 0.5068 | 0.802 | 0.4286 | 0.0462 | 0.0833 | 1.4495 |
| 0.4619 | 6.0 | 1500 | 0.5153 | 0.795 | 0.4074 | 0.1128 | 0.1767 | 1.4637 |
| 0.4619 | 7.0 | 1750 | 0.5246 | 0.795 | 0.3611 | 0.0667 | 0.1126 | 1.4472 |
| 0.3988 | 8.0 | 2000 | 0.6671 | 0.797 | 0.3333 | 0.0410 | 0.0731 | 1.4407 |
| 0.3988 | 9.0 | 2250 | 0.6091 | 0.763 | 0.35 | 0.2513 | 0.2925 | 1.4680 |
| 0.3128 | 10.0 | 2500 | 0.7342 | 0.759 | 0.3284 | 0.2256 | 0.2675 | 1.4535 |
| 0.3128 | 11.0 | 2750 | 0.8236 | 0.741 | 0.3049 | 0.2564 | 0.2786 | 1.4391 |
| 0.2198 | 12.0 | 3000 | 0.9349 | 0.742 | 0.3297 | 0.3128 | 0.3211 | 1.4601 |
| 0.2198 | 13.0 | 3250 | 1.1979 | 0.764 | 0.3481 | 0.2410 | 0.2848 | 1.4658 |
| 0.1522 | 14.0 | 3500 | 1.3995 | 0.758 | 0.3464 | 0.2718 | 0.3046 | 1.4682 |
| 0.1522 | 15.0 | 3750 | 2.3304 | 0.779 | 0.3143 | 0.1128 | 0.1660 | 1.4414 |
| 0.1137 | 16.0 | 4000 | 2.0930 | 0.762 | 0.2991 | 0.1641 | 0.2119 | 1.4359 |
| 0.1137 | 17.0 | 4250 | 2.6869 | 0.787 | 0.3714 | 0.1333 | 0.1962 | 1.4598 |
| 0.0904 | 18.0 | 4500 | 2.2347 | 0.678 | 0.2818 | 0.4205 | 0.3374 | 1.4071 |
| 0.0904 | 19.0 | 4750 | 2.4580 | 0.752 | 0.3221 | 0.2462 | 0.2791 | 1.4509 |
| 0.0737 | 20.0 | 5000 | 2.4906 | 0.743 | 0.3038 | 0.2462 | 0.2720 | 1.4383 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
