Whisper Small Spanish
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 es dataset. It achieves the following results on the evaluation set:
- Loss: 0.2210
- Wer: 8.2123
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1386 | 4.01 | 1000 | 0.2464 | 9.8000 |
| 0.1098 | 8.01 | 2000 | 0.2272 | 8.6229 |
| 0.028 | 12.02 | 3000 | 0.2577 | 8.6956 |
| 0.1083 | 16.02 | 4000 | 0.2210 | 8.2123 |
| 0.0189 | 20.03 | 5000 | 0.2520 | 8.4455 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3
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Dataset used to train danielizham/whisper-small-es
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 estest set self-reported8.212