Whisper Medium Mixed-Portuguese
This model is a fine-tuned version of openai/whisper-medium on the pt datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
It achieves the following results on the evaluation set:
- Loss: 0.1353
- Wer: 7.1230
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: 32
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1116 | 0.2 | 1000 | 0.1570 | 8.5824 |
| 0.105 | 0.4 | 2000 | 0.1484 | 7.9398 |
| 0.0783 | 0.6 | 3000 | 0.1374 | 7.4475 |
| 0.1703 | 0.8 | 4000 | 0.1370 | 7.2413 |
| 0.0977 | 1.0622 | 5000 | 0.1353 | 7.1230 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1