ber3
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0476
- F1: 0.0
- Roc Auc: 0.5
- Accuracy: 0.0
- F1-macro: 0.0
- Precision-micro: 0.0
- Precision-macro: 0.0
- Recall-micro: 0.0
- Recall-macro: 0.0
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | F1-macro | Precision-micro | Precision-macro | Recall-micro | Recall-macro |
|---|
| No log | 1.0 | 121 | 0.2031 | 0.0046 | 0.5116 | 0.0 | 0.0006 | 0.0023 | 0.0003 | 0.1458 | 0.0611 |
| No log | 2.0 | 242 | 0.0893 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 363 | 0.0609 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 4.0 | 484 | 0.0505 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.1695 | 5.0 | 605 | 0.0476 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
