Whisper Medium Breton
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 br dataset. It achieves the following results on the evaluation set:
- Loss: 0.8486
- Wer: 41.6117
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: 4e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0602 | 5.03 | 1000 | 0.7324 | 43.6957 |
| 0.0036 | 10.05 | 2000 | 0.8486 | 41.6117 |
| 0.001 | 15.08 | 3000 | 0.9033 | 42.0458 |
| 0.0004 | 20.1 | 4000 | 0.9351 | 41.6811 |
| 0.0003 | 25.13 | 5000 | 0.9468 | 41.7853 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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Dataset used to train BlueRaccoon/whisper-medium-br
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 brtest set self-reported41.612