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ssc-ush-mms-model-mix-adapt-max-longcv2
ctaguchi/ssc-ush-mms-model-mix-adapt-max-longcv2
ssc-ush-mms-model-mix-adapt-max-longcv2 is a automatic speech recognition model from ctaguchi. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Dec 10, 2025
- Updated
- Dec 10, 2025
- SHA
- cb94cbe5
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
ssc-ush-mms-model-mix-adapt-max-longcv2
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: 0.5479
- Cer: 0.1241
- Wer: 0.4626
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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|---|---|---|---|---|---|
| 0.7025 | 3.125 | 200 | 0.5108 | 0.1573 | 0.5156 |
| 0.4765 | 6.25 | 400 | 0.4266 | 0.1213 | 0.4428 |
| 0.3969 | 9.375 | 600 | 0.4061 | 0.1217 | 0.4158 |
| 0.3477 | 12.5 | 800 | 0.4071 | 0.1241 | 0.4272 |
| 0.3402 | 15.625 | 1000 | 0.3838 | 0.1132 | 0.4044 |
| 0.3649 | 18.75 | 1200 | 0.4015 | 0.1206 | 0.4148 |
| 0.6528 | 21.875 | 1400 | 0.6619 | 0.1336 | 0.4886 |
| 0.5894 | 25.0 | 1600 | 0.4972 | 0.1197 | 0.4459 |
| 0.5353 | 28.125 | 1800 | 0.5479 | 0.1241 | 0.4626 |
Framework versions
- Transformers 4.52.1
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- cc-by-nc-4.0
- Created
- Dec 10, 2025
- Updated
- Dec 10, 2025