full-pos
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: 0.0980
- Accuracy: 0.9762
- F1 Macro: 0.9377
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: 32
- eval_batch_size: 64
- seed: 42
- 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
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 0.0946 | 1.0 | 392 | 0.1062 | 0.9699 | 0.9001 |
| 0.0513 | 2.0 | 784 | 0.0986 | 0.9727 | 0.9258 |
| 0.0341 | 3.0 | 1176 | 0.1018 | 0.9740 | 0.9348 |
| 0.0207 | 4.0 | 1568 | 0.1077 | 0.9743 | 0.9343 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.23.1