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: 0.1107
- Wer: 4.4260
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: 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: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.186 | 0.2 | 500 | 0.1487 | 6.1786 |
| 0.1947 | 0.4 | 1000 | 0.1350 | 5.5910 |
| 0.3566 | 0.6 | 1500 | 0.1242 | 4.9537 |
| 0.1237 | 0.8 | 2000 | 0.1181 | 4.8001 |
| 0.1902 | 1.0 | 2500 | 0.1107 | 4.4260 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.0
- Datasets 2.6.2.dev0
- Tokenizers 0.12.1
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