Whisper Base Portugese Punctuation 5k - Chee Li
This model is a fine-tuned version of openai/whisper-base on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.7189
- Wer: 94.7594
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.143 | 5.0251 | 1000 | 0.5439 | 109.9784 |
| 0.0159 | 10.0503 | 2000 | 0.6498 | 93.6172 |
| 0.0059 | 15.0754 | 3000 | 0.7012 | 100.0188 |
| 0.0045 | 20.1005 | 4000 | 0.7189 | 94.7594 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.3
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Base model
openai/whisper-base