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distilbert-base-uncased_fold_2_ternary
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: 1.5810
- F1: 0.7620
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 | 294 | 0.5886 | 0.7239 |
| 0.557 | 2.0 | 588 | 0.5085 | 0.7524 |
| 0.557 | 3.0 | 882 | 0.6332 | 0.7530 |
| 0.2456 | 4.0 | 1176 | 0.8749 | 0.7161 |
| 0.2456 | 5.0 | 1470 | 1.0601 | 0.7371 |
| 0.1112 | 6.0 | 1764 | 1.1885 | 0.7451 |
| 0.0484 | 7.0 | 2058 | 1.3027 | 0.7240 |
| 0.0484 | 8.0 | 2352 | 1.4647 | 0.7259 |
| 0.0259 | 9.0 | 2646 | 1.4476 | 0.7322 |
| 0.0259 | 10.0 | 2940 | 1.4826 | 0.7388 |
| 0.0164 | 11.0 | 3234 | 1.5869 | 0.7333 |
| 0.0109 | 12.0 | 3528 | 1.5954 | 0.7539 |
| 0.0109 | 13.0 | 3822 | 1.5810 | 0.7620 |
| 0.0082 | 14.0 | 4116 | 1.7165 | 0.7335 |
| 0.0082 | 15.0 | 4410 | 1.8152 | 0.7414 |
| 0.004 | 16.0 | 4704 | 1.7411 | 0.7474 |
| 0.004 | 17.0 | 4998 | 1.8692 | 0.7355 |
| 0.0034 | 18.0 | 5292 | 1.8727 | 0.7303 |
| 0.0009 | 19.0 | 5586 | 1.9813 | 0.7305 |
| 0.0009 | 20.0 | 5880 | 1.9764 | 0.7391 |
| 0.0012 | 21.0 | 6174 | 2.0170 | 0.7291 |
| 0.0012 | 22.0 | 6468 | 2.0240 | 0.7391 |
| 0.0004 | 23.0 | 6762 | 2.0311 | 0.7352 |
| 0.0014 | 24.0 | 7056 | 2.0174 | 0.7334 |
| 0.0014 | 25.0 | 7350 | 2.0282 | 0.7381 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
