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fine-tuned-five-classes
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: 0.2424
- F1: 0.8905
- Roc Auc: 0.9138
- Accuracy: 0.6825
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 250 | 0.2669 | 0.8759 | 0.9008 | 0.6525 |
| 0.3273 | 2.0 | 500 | 0.2424 | 0.8905 | 0.9138 | 0.6825 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.1+cpu
- Datasets 2.8.0
- Tokenizers 0.12.1
