results
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: 0.4186
- Accuracy: 0.9028
- Precision: 0.7440
- Recall: 0.6525
- F1: 0.6953
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.238 | 1.0 | 347 | 0.2861 | 0.8913 | 0.7179 | 0.5932 | 0.6497 |
| 0.2052 | 2.0 | 694 | 0.2654 | 0.9057 | 0.7966 | 0.5975 | 0.6828 |
| 0.024 | 3.0 | 1041 | 0.4186 | 0.9028 | 0.7440 | 0.6525 | 0.6953 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Tokenizers 0.19.1
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Base model
google-bert/bert-base-uncased