visobert
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7190
- Accuracy: 0.8800
- F1: 0.8772
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: 128
- eval_batch_size: 128
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 90 | 0.7585 | 0.8623 | 0.8485 |
| 0.9017 | 2.0 | 180 | 0.7163 | 0.8654 | 0.8548 |
| 0.9017 | 3.0 | 270 | 0.6744 | 0.8768 | 0.8732 |
| 0.5148 | 4.0 | 360 | 0.7341 | 0.8699 | 0.8635 |
| 0.5148 | 5.0 | 450 | 0.7190 | 0.8800 | 0.8772 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Downloads last month
- 9