Whisper Small Es - Sanchit Gandhi
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: 0.1883
- Wer: 6.0743
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: 32
- eval_batch_size: 16
- seed: 42
- 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 |
|---|---|---|---|---|
| 0.0694 | 0.2 | 1000 | 0.2194 | 6.8194 |
| 0.0336 | 0.4 | 2000 | 0.2097 | 6.7558 |
| 0.0221 | 0.6 | 3000 | 0.2068 | 6.4952 |
| 0.0266 | 0.8 | 4000 | 0.1950 | 6.2841 |
| 0.0256 | 1.0 | 5000 | 0.1883 | 6.0743 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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