ssc-bew-mms-model-mix-adapt-max
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6537
- Cer: 0.1746
- Wer: 0.5203
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: 0.001
- train_batch_size: 2
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 0.648 | 0.9828 | 200 | 0.6882 | 0.1821 | 0.5469 |
| 0.6337 | 1.9631 | 400 | 0.6792 | 0.1797 | 0.5336 |
| 0.5803 | 2.9435 | 600 | 0.6627 | 0.1774 | 0.5296 |
| 0.5773 | 3.9238 | 800 | 0.6562 | 0.1759 | 0.5236 |
| 0.5492 | 4.9042 | 1000 | 0.6537 | 0.1746 | 0.5203 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.0
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