qevasion_flat_1782203160
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7099
- Accuracy: 0.3333
- Precision Macro: 0.1519
- Recall Macro: 0.1532
- F1 Macro: 0.1280
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: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 120
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro |
|---|---|---|---|---|---|---|---|
| 1.9698 | 1.0 | 259 | 1.8661 | 0.3101 | 0.1082 | 0.1142 | 0.0582 |
| 1.8544 | 2.0 | 518 | 1.8761 | 0.3072 | 0.0623 | 0.1132 | 0.0582 |
| 1.7084 | 3.0 | 777 | 1.7099 | 0.3333 | 0.1519 | 0.1532 | 0.1280 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2