FT-XS
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 9.6372
- Wer: 0.4228
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.2153 | 0.85 | 500 | 19.9974 | 1.0136 |
| 2.1468 | 1.7 | 1000 | 11.1663 | 0.7427 |
| 0.9386 | 2.56 | 1500 | 8.9351 | 0.5688 |
| 0.7167 | 3.41 | 2000 | 8.2026 | 0.5132 |
| 0.6266 | 4.26 | 2500 | 7.9430 | 0.4786 |
| 0.5402 | 5.11 | 3000 | 8.2822 | 0.4560 |
| 0.4953 | 5.96 | 3500 | 8.3400 | 0.4429 |
| 0.4531 | 6.81 | 4000 | 8.7580 | 0.4393 |
| 0.4389 | 7.67 | 4500 | 9.8518 | 0.4308 |
| 0.4348 | 8.52 | 5000 | 9.5559 | 0.4246 |
| 0.4091 | 9.37 | 5500 | 9.6372 | 0.4228 |
Framework versions
- Transformers 4.17.0
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2
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