mms_sesame_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: 1.9116
- Wer: 0.5995
- Cer: 0.3471
- Bertscore Precision: 0.6224
- Bertscore Recall: 0.6664
- Bertscore F1: 0.6400
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 |
|---|---|---|---|---|---|---|---|---|
| 1.9216 | 21.0085 | 500 | 1.6593 | 0.5909 | 0.3361 | 0.6275 | 0.6691 | 0.6440 |
| 1.7172 | 43.0055 | 1000 | 1.7099 | 0.6058 | 0.3503 | 0.6315 | 0.6703 | 0.6469 |
| 1.302 | 65.0025 | 1500 | 1.7937 | 0.5971 | 0.3442 | 0.6320 | 0.6731 | 0.6484 |
| 1.0859 | 86.011 | 2000 | 1.9116 | 0.5995 | 0.3471 | 0.6224 | 0.6664 | 0.6400 |
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_sesame_knn_vc
Base model
facebook/mms-1b-all