Whisper Tiny Ro (local) - Augustin Jianu
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5978
- Wer: 37.4835
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 OptimizerNames.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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4417 | 1.7730 | 1000 | 0.5327 | 43.8513 |
| 0.1813 | 3.5461 | 2000 | 0.4666 | 38.8689 |
| 0.0751 | 5.3191 | 3000 | 0.4645 | 36.5006 |
| 0.0326 | 7.0922 | 4000 | 0.4803 | 36.4614 |
| 0.0234 | 8.8652 | 5000 | 0.5087 | 36.5148 |
| 0.0082 | 10.6383 | 6000 | 0.5424 | 36.6252 |
| 0.0042 | 12.4113 | 7000 | 0.5650 | 37.6509 |
| 0.0029 | 14.1844 | 8000 | 0.5809 | 36.8710 |
| 0.0025 | 15.9574 | 9000 | 0.5922 | 38.1495 |
| 0.0021 | 17.7305 | 10000 | 0.5978 | 37.4835 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
openai/whisper-tiny