Whisper Small SV
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3516
- Wer: 23.0598
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3274 | 0.86 | 200 | 0.3552 | 24.7469 |
| 0.1395 | 1.72 | 400 | 0.3303 | 23.5038 |
| 0.074 | 2.59 | 600 | 0.3349 | 22.6603 |
| 0.0199 | 3.45 | 800 | 0.3451 | 22.7935 |
| 0.0089 | 4.31 | 1000 | 0.3516 | 23.0598 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
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