Whisper Small Es - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-medium on the Multilingual LibriSpeech dataset. It achieves the following results on the evaluation set:
- Loss: 0.1694
- Wer: 7.3696
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-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7733 | 0.25 | 1000 | 0.6193 | 17.9946 |
| 0.2991 | 0.5 | 2000 | 0.3162 | 14.2555 |
| 0.2929 | 0.75 | 3000 | 0.1799 | 7.7752 |
| 0.3099 | 1.0 | 4000 | 0.1694 | 7.3696 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.0
- Datasets 2.6.2.dev0
- Tokenizers 0.12.1
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