heb-verifier17-connected
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0546
- Cer: 0.0209
- Exact: 0.9619
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 0.05
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Exact |
|---|
| 0.1357 | 0.3729 | 500 | 0.1282 | 0.0503 | 0.9104 |
| 0.1084 | 0.7457 | 1000 | 0.0856 | 0.0362 | 0.9384 |
| 0.0478 | 1.1186 | 1500 | 0.0732 | 0.0260 | 0.9518 |
| 0.0625 | 1.4914 | 2000 | 0.0542 | 0.0215 | 0.9630 |
| 0.0567 | 1.8643 | 2500 | 0.0567 | 0.0220 | 0.9597 |
| 0.0336 | 2.2371 | 3000 | 0.0473 | 0.0209 | 0.9619 |
| 0.0427 | 2.6100 | 3500 | 0.0334 | 0.0164 | 0.9720 |
| 0.0354 | 2.9828 | 4000 | 0.0370 | 0.0153 | 0.9709 |
| 0.0354 | 3.0 | 4023 | 0.0546 | 0.0209 | 0.9619 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
