Whisper Tiny Portuguese 5000 - Chee Li
This model is a fine-tuned version of openai/whisper-tiny on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.6510
- Wer: 102.8207
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: 625
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1445 | 5.0251 | 1000 | 0.5040 | 109.3037 |
0.0131 | 10.0503 | 2000 | 0.5788 | 110.2628 |
0.0043 | 15.0754 | 3000 | 0.6183 | 112.4207 |
0.0027 | 20.1005 | 4000 | 0.6429 | 109.2708 |
0.0022 | 25.1256 | 5000 | 0.6510 | 102.8207 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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openai/whisper-tiny