newly_fine_tuned_bert
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0615
- F1: 0.5714
- Roc Auc: 0.7
- Accuracy: 0.4
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: 200
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.0375 | 80.0 | 1760 | 0.0726 | 0.4 | 0.625 | 0.25 |
| 0.0166 | 160.0 | 3520 | 0.0615 | 0.5714 | 0.7 | 0.4 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
google-bert/bert-base-uncased