Whisper-Tiny-PTBR
This model is a fine-tuned version of openai/whisper-tiny on the nurc-sp_pseudo_labelled dataset. It achieves the following results on the evaluation set:
- Loss: 1.0137
- Wer: 59.3804
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: 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 |
|---|---|---|---|---|
| 1.2522 | 0.5094 | 1000 | 1.1713 | 74.6895 |
| 1.0397 | 1.0188 | 2000 | 1.0796 | 68.5537 |
| 0.9879 | 1.5283 | 3000 | 1.0420 | 62.4686 |
| 0.9334 | 2.0377 | 4000 | 1.0195 | 59.7845 |
| 0.9834 | 2.5471 | 5000 | 1.0137 | 59.3804 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-tiny