Whisper Fine-tuning Event: Winning Models
Collection
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Whisper Large V2 Breton
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 br dataset. It achieves the following results on the evaluation set:
- Loss: 0.6425
- Wer: 35.1077
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0065 | 5.03 | 3000 | 0.6425 | 35.1077 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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Dataset used to train DrishtiSharma/whisper-large-v2-breton-3k-steps
Collection including DrishtiSharma/whisper-large-v2-breton-3k-steps
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 brtest set self-reported35.108