whisper-small-or
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: 0.5871
- Wer: 40.3061
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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.001 | 25.01 | 1000 | 0.4038 | 37.4804 |
| 0.0001 | 51.0 | 2000 | 0.5288 | 40.0706 |
| 0.0001 | 76.01 | 3000 | 0.5871 | 40.3061 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.10.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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