ssc-meh-mms-model-mix-adapt-max2
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9357
- Cer: 0.1848
- Wer: 0.5245
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: 1
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Use OptimizerNames.ADAMW_TORCH 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 |
|---|---|---|---|---|---|
| 0.3852 | 0.6231 | 200 | 0.9490 | 0.1866 | 0.5388 |
| 0.3834 | 1.2461 | 400 | 0.8982 | 0.1913 | 0.5373 |
| 0.3539 | 1.8692 | 600 | 0.9107 | 0.1877 | 0.5265 |
| 0.3641 | 2.4922 | 800 | 0.9277 | 0.1873 | 0.5250 |
| 0.3281 | 3.1153 | 1000 | 0.9339 | 0.1895 | 0.5360 |
| 0.3245 | 3.7383 | 1200 | 0.9323 | 0.1871 | 0.5261 |
| 0.2834 | 4.3614 | 1400 | 0.9389 | 0.1841 | 0.5205 |
| 0.278 | 4.9844 | 1600 | 0.9357 | 0.1848 | 0.5245 |
Framework versions
- Transformers 4.52.1
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4
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