wav2vec2-large-mms-1b-uyghur-latin
This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following best results on the evaluation set:
- Best Wer: 30.8949%
- Best Cer: 5.9823 %
Training procedure
Finetuning code avaiblable in https://github.com/ixxan/ug-speech
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: 4
- total_train_batch_size: 32
- optimizer: Use 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: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Cer Ortho |
|---|---|---|---|---|---|
| 0.3425 | 1.0006 | 1313 | 0.3081 | 35.3122 | 6.8424 |
| 0.3218 | 2.0011 | 2626 | 0.2771 | 31.7204 | 6.1840 |
| 0.3012 | 3.0017 | 3939 | 0.2739 | 30.8949 | 5.9823 |
| 0.2961 | 3.9989 | 5248 | 0.2771 | 31.7116 | 6.1806 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3