testing_params_cair1
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0914
- F1: 0.9609
- Roc Auc: 0.9657
- Accuracy: 0.8862
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 248 | 0.2621 | 0.8898 | 0.9140 | 0.6748 |
| No log | 2.0 | 496 | 0.2282 | 0.8700 | 0.8909 | 0.6504 |
| 0.3113 | 3.0 | 744 | 0.1869 | 0.9168 | 0.9332 | 0.7561 |
| 0.3113 | 4.0 | 992 | 0.1627 | 0.9247 | 0.9384 | 0.7805 |
| 0.1955 | 5.0 | 1240 | 0.1440 | 0.9316 | 0.9404 | 0.8049 |
| 0.1955 | 6.0 | 1488 | 0.1263 | 0.9455 | 0.9532 | 0.8455 |
| 0.1343 | 7.0 | 1736 | 0.1087 | 0.9478 | 0.9553 | 0.8537 |
| 0.1343 | 8.0 | 1984 | 0.0951 | 0.9567 | 0.9630 | 0.8862 |
| 0.0874 | 9.0 | 2232 | 0.0937 | 0.9609 | 0.9657 | 0.8862 |
| 0.0874 | 10.0 | 2480 | 0.0914 | 0.9609 | 0.9657 | 0.8862 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.12.1+cpu
- Datasets 2.9.0
- Tokenizers 0.12.1