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gpt2_small
This model is a fine-tuned version of 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 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
