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Whisper Small Italian - Robust
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 it dataset. It achieves the following results on the evaluation set:
- Loss: 0.1980
- Wer: 8.7457
IMPORTANT The model has been trained using data augmentation to improve its generalization capabilities and robustness. The results on the eval set during training are biased towards data augmentation applied to evaluation data.
Results on eval set
- Mozilla CV 11.0 - Italian: 8.00 wer (using official script)
- TODO
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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: 25000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1927 | 1.0 | 2500 | 0.2506 | 14.9991 |
| 0.0736 | 2.01 | 5000 | 0.2258 | 12.7864 |
| 0.0413 | 3.01 | 7500 | 0.2144 | 11.4508 |
| 0.0201 | 4.02 | 10000 | 0.2146 | 10.8774 |
| 0.0129 | 5.02 | 12500 | 0.2127 | 10.6920 |
| 0.0091 | 6.03 | 15000 | 0.2117 | 10.2867 |
| 0.0043 | 7.03 | 17500 | 0.2076 | 9.6860 |
| 0.0018 | 8.04 | 20000 | 0.2065 | 9.4235 |
| 0.0013 | 9.04 | 22500 | 0.2003 | 8.9105 |
| 0.0009 | 10.05 | 25000 | 0.1978 | 8.7497 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
