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Whisper Small Portuguese
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 pt dataset. It achieves the following results on the evaluation set:
- Loss: 0.3023
- Wer: 14.2373
- Cer: 5.5236
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.1113 | 0.92 | 500 | 0.3897 | 16.8721 | 6.7919 |
| 0.9009 | 1.84 | 1000 | 0.3318 | 15.9322 | 6.2310 |
| 0.7631 | 2.76 | 1500 | 0.3177 | 15.4854 | 5.8939 |
| 0.7163 | 3.68 | 2000 | 0.3130 | 14.8998 | 5.7972 |
| 0.6334 | 4.6 | 2500 | 0.3034 | 14.7920 | 5.6867 |
| 0.5746 | 5.52 | 3000 | 0.3029 | 14.6225 | 5.6397 |
| 0.5359 | 6.45 | 3500 | 0.3018 | 14.4838 | 5.5789 |
| 0.5058 | 7.37 | 4000 | 0.3010 | 14.5917 | 5.6839 |
| 0.4833 | 8.29 | 4500 | 0.3023 | 14.2373 | 5.5236 |
| 0.4398 | 9.21 | 5000 | 0.3005 | 14.4222 | 5.5844 |
| 0.4359 | 10.13 | 5500 | 0.2999 | 14.4838 | 5.6259 |
| 0.4036 | 11.05 | 6000 | 0.2995 | 14.2835 | 5.5623 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
