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distilbert-base-uncased_fold_6_ternary_v1
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9031
- F1: 0.7910
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: 2e-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
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 292 | 0.5235 | 0.7769 |
| 0.566 | 2.0 | 584 | 0.5268 | 0.7923 |
| 0.566 | 3.0 | 876 | 0.6189 | 0.7756 |
| 0.2514 | 4.0 | 1168 | 0.7777 | 0.8026 |
| 0.2514 | 5.0 | 1460 | 0.9380 | 0.7936 |
| 0.1175 | 6.0 | 1752 | 1.0957 | 0.7872 |
| 0.0579 | 7.0 | 2044 | 1.2370 | 0.7923 |
| 0.0579 | 8.0 | 2336 | 1.3739 | 0.7936 |
| 0.0259 | 9.0 | 2628 | 1.3457 | 0.7846 |
| 0.0259 | 10.0 | 2920 | 1.4938 | 0.7872 |
| 0.0125 | 11.0 | 3212 | 1.5921 | 0.7885 |
| 0.0108 | 12.0 | 3504 | 1.6504 | 0.7897 |
| 0.0108 | 13.0 | 3796 | 1.7532 | 0.7756 |
| 0.007 | 14.0 | 4088 | 1.7029 | 0.7821 |
| 0.007 | 15.0 | 4380 | 1.7632 | 0.7987 |
| 0.0067 | 16.0 | 4672 | 1.7084 | 0.7962 |
| 0.0067 | 17.0 | 4964 | 1.7559 | 0.7962 |
| 0.0072 | 18.0 | 5256 | 1.8431 | 0.7987 |
| 0.0028 | 19.0 | 5548 | 1.8689 | 0.7846 |
| 0.0028 | 20.0 | 5840 | 1.8641 | 0.7885 |
| 0.0033 | 21.0 | 6132 | 1.8578 | 0.7923 |
| 0.0033 | 22.0 | 6424 | 1.9071 | 0.7833 |
| 0.003 | 23.0 | 6716 | 1.8959 | 0.7872 |
| 0.0011 | 24.0 | 7008 | 1.9073 | 0.7987 |
| 0.0011 | 25.0 | 7300 | 1.9031 | 0.7910 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
