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distilbert-base-uncased_fold_1_binary
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: 1.5992
- F1: 0.7687
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 | 288 | 0.3960 | 0.7467 |
| 0.3988 | 2.0 | 576 | 0.3947 | 0.7487 |
| 0.3988 | 3.0 | 864 | 0.4511 | 0.7662 |
| 0.1853 | 4.0 | 1152 | 0.7226 | 0.7285 |
| 0.1853 | 5.0 | 1440 | 0.9398 | 0.7334 |
| 0.0827 | 6.0 | 1728 | 1.0547 | 0.7427 |
| 0.0287 | 7.0 | 2016 | 1.1602 | 0.7563 |
| 0.0287 | 8.0 | 2304 | 1.3332 | 0.7171 |
| 0.0219 | 9.0 | 2592 | 1.3429 | 0.7420 |
| 0.0219 | 10.0 | 2880 | 1.2603 | 0.7648 |
| 0.0139 | 11.0 | 3168 | 1.4126 | 0.7569 |
| 0.0139 | 12.0 | 3456 | 1.3195 | 0.7483 |
| 0.0115 | 13.0 | 3744 | 1.4356 | 0.7491 |
| 0.0035 | 14.0 | 4032 | 1.5693 | 0.7636 |
| 0.0035 | 15.0 | 4320 | 1.4071 | 0.7662 |
| 0.0071 | 16.0 | 4608 | 1.4561 | 0.7579 |
| 0.0071 | 17.0 | 4896 | 1.5405 | 0.7634 |
| 0.0041 | 18.0 | 5184 | 1.5862 | 0.7589 |
| 0.0041 | 19.0 | 5472 | 1.6782 | 0.76 |
| 0.0024 | 20.0 | 5760 | 1.5699 | 0.7677 |
| 0.0006 | 21.0 | 6048 | 1.5991 | 0.7467 |
| 0.0006 | 22.0 | 6336 | 1.6205 | 0.7682 |
| 0.0003 | 23.0 | 6624 | 1.6334 | 0.7643 |
| 0.0003 | 24.0 | 6912 | 1.5992 | 0.7687 |
| 0.0011 | 25.0 | 7200 | 1.6053 | 0.7624 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
