mms_knn_vc
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: 1.6851
- Wer: 0.5400
- Cer: 0.3424
- Bertscore Precision: 0.6802
- Bertscore Recall: 0.7134
- Bertscore F1: 0.6932
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: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch_fused 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: 50
- training_steps: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|---|---|---|---|---|---|---|---|---|
| 1.3967 | 19.0125 | 500 | 1.5072 | 0.5607 | 0.3355 | 0.6606 | 0.6987 | 0.6757 |
| 1.1303 | 39.0125 | 1000 | 1.5313 | 0.5439 | 0.3280 | 0.6681 | 0.7061 | 0.6832 |
| 0.897 | 59.0125 | 1500 | 1.6450 | 0.5506 | 0.3428 | 0.6727 | 0.7083 | 0.6867 |
| 0.8015 | 79.0125 | 2000 | 1.6851 | 0.5400 | 0.3424 | 0.6802 | 0.7134 | 0.6932 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
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Model tree for resproj007/mms_knn_vc
Base model
facebook/mms-1b-all