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distilbert-base-uncased_fold_2_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: 0.4724
- F1: 0.7604
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 | 290 | 0.4280 | 0.7515 |
| 0.4018 | 2.0 | 580 | 0.4724 | 0.7604 |
| 0.4018 | 3.0 | 870 | 0.5336 | 0.7428 |
| 0.1995 | 4.0 | 1160 | 0.8367 | 0.7476 |
| 0.1995 | 5.0 | 1450 | 0.9242 | 0.7412 |
| 0.089 | 6.0 | 1740 | 1.0987 | 0.7410 |
| 0.0318 | 7.0 | 2030 | 1.1853 | 0.7584 |
| 0.0318 | 8.0 | 2320 | 1.2509 | 0.7500 |
| 0.0189 | 9.0 | 2610 | 1.5060 | 0.7258 |
| 0.0189 | 10.0 | 2900 | 1.5607 | 0.7534 |
| 0.0084 | 11.0 | 3190 | 1.5871 | 0.7476 |
| 0.0084 | 12.0 | 3480 | 1.7206 | 0.7338 |
| 0.0047 | 13.0 | 3770 | 1.6776 | 0.7340 |
| 0.0068 | 14.0 | 4060 | 1.7339 | 0.7546 |
| 0.0068 | 15.0 | 4350 | 1.8279 | 0.7504 |
| 0.0025 | 16.0 | 4640 | 1.7791 | 0.7411 |
| 0.0025 | 17.0 | 4930 | 1.7917 | 0.7444 |
| 0.003 | 18.0 | 5220 | 1.7781 | 0.7559 |
| 0.0029 | 19.0 | 5510 | 1.8153 | 0.7559 |
| 0.0029 | 20.0 | 5800 | 1.7757 | 0.7414 |
| 0.0055 | 21.0 | 6090 | 1.8635 | 0.7454 |
| 0.0055 | 22.0 | 6380 | 1.8483 | 0.7460 |
| 0.001 | 23.0 | 6670 | 1.8620 | 0.7492 |
| 0.001 | 24.0 | 6960 | 1.9058 | 0.7508 |
| 0.0006 | 25.0 | 7250 | 1.8640 | 0.7504 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
