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Whisper Medium Greek - Robust
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 el dataset. It achieves the following results on the evaluation set:
- Loss: 0.2807
- Wer: 17.7099
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 - Greek: 13.250 WER (using official script)
- Google Fluers - Greek: 39.59 WER (using official script)
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: 8
- eval_batch_size: 4
- 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: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0407 | 4.69 | 2000 | 0.2484 | 20.8767 |
| 0.0128 | 9.39 | 4000 | 0.2795 | 21.2017 |
| 0.0041 | 14.08 | 6000 | 0.2744 | 19.1308 |
| 0.0017 | 18.78 | 8000 | 0.2759 | 17.9978 |
| 0.0005 | 23.47 | 10000 | 0.2751 | 18.5457 |
| 0.0015 | 28.17 | 12000 | 0.2928 | 19.2051 |
| 0.0004 | 32.86 | 14000 | 0.2819 | 18.2857 |
| 0.0002 | 37.56 | 16000 | 0.2831 | 17.7285 |
| 0.0007 | 42.25 | 18000 | 0.2776 | 17.8399 |
| 0.0 | 46.95 | 20000 | 0.2792 | 17.0970 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.7.1
- Tokenizers 0.12.1
