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bipolarvsN
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: 0.7437
- F1: 0.7833
- Roc Auc: 0.7818
- Accuracy: 0.7833
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 |
|---|---|---|---|---|---|---|
| 0.5251 | 1.0 | 875 | 0.5404 | 0.736 | 0.7299 | 0.736 |
| 0.4396 | 2.0 | 1750 | 0.4694 | 0.7974 | 0.7966 | 0.7974 |
| 0.373 | 3.0 | 2625 | 0.5041 | 0.797 | 0.7963 | 0.797 |
| 0.2828 | 4.0 | 3500 | 0.6178 | 0.7939 | 0.7931 | 0.7939 |
| 0.2147 | 5.0 | 4375 | 0.7437 | 0.7833 | 0.7818 | 0.7833 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
