ssc-ush-mms-model-mix-adapt-max2
This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3773
- Cer: 0.1160
- Wer: 0.4158
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: 8
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 0.7005 | 3.2810 | 200 | 0.5252 | 0.1484 | 0.5239 |
| 0.4747 | 6.5620 | 400 | 0.4337 | 0.1280 | 0.4480 |
| 0.3834 | 9.8430 | 600 | 0.4022 | 0.1260 | 0.4439 |
| 0.3294 | 13.1157 | 800 | 0.3773 | 0.1160 | 0.4158 |
Framework versions
- Transformers 4.52.1
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4
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Model tree for ctaguchi/ssc-ush-mms-model-mix-adapt-max2
Base model
facebook/mms-1b-all