cf-bert-finetuned1-hg
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: 0.3333
- F1: 0.5695
- Roc Auc: 0.7144
- Accuracy: 0.2665
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.3849 | 1.0 | 893 | 0.3797 | 0.4709 | 0.6593 | 0.1803 |
| 0.324 | 2.0 | 1786 | 0.3518 | 0.5319 | 0.6915 | 0.2296 |
| 0.3079 | 3.0 | 2679 | 0.3478 | 0.5524 | 0.7051 | 0.2430 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1