ssc-ush-mms-model-mix-adapt-max-longcv
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: 0.4095
- Cer: 0.1221
- Wer: 0.4335
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: 8
- 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 |
|---|---|---|---|---|---|
| 4.0319 | 3.125 | 200 | 3.2006 | 0.9733 | 1.0 |
| 0.5929 | 6.25 | 400 | 0.4704 | 0.1349 | 0.5062 |
| 0.4709 | 9.375 | 600 | 0.4133 | 0.1243 | 0.4387 |
| 0.4233 | 12.5 | 800 | 0.4095 | 0.1221 | 0.4335 |
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-max-longcv
Base model
facebook/mms-1b-all