Whisper Small Hre 3.1 - 600 steps, metric CER
This model is a fine-tuned version of openai/whisper-small on the Hre audio dataset 3 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2948
- Cer Ortho: 27.1607
- Cer: 24.7789
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 600
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer Ortho | Cer |
|---|---|---|---|---|---|
| 0.0299 | 6.38 | 600 | 1.2948 | 27.1607 | 24.7789 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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