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: 0.1252
- Wer: 4.9888
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: 8
- 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: 500
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2346 | 0.2 | 500 | 0.1957 | 8.5131 |
| 0.1252 | 0.4 | 1000 | 0.1448 | 5.7876 |
| 0.2076 | 0.6 | 1500 | 0.1361 | 5.5786 |
| 0.2356 | 0.8 | 2000 | 0.1504 | 6.6611 |
| 0.1893 | 1.0 | 2500 | 0.1252 | 4.9888 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.0
- Datasets 2.6.2.dev0
- Tokenizers 0.12.1
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