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ptsdvsN
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0050
- F1: 0.8051
- Roc Auc: 0.8042
- Accuracy: 0.8051
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: 5e-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 |
|---|---|---|---|---|---|---|
| 0.4907 | 1.0 | 875 | 0.4679 | 0.8161 | 0.8164 | 0.8161 |
| 0.3568 | 2.0 | 1750 | 0.4654 | 0.8221 | 0.8225 | 0.8221 |
| 0.2289 | 3.0 | 2625 | 0.7412 | 0.7843 | 0.7800 | 0.7843 |
| 0.1246 | 4.0 | 3500 | 0.8720 | 0.8013 | 0.7995 | 0.8013 |
| 0.0656 | 5.0 | 4375 | 1.0050 | 0.8051 | 0.8042 | 0.8051 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
