Whisper Small Greek - Robust
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 el dataset. It achieves the following results on the evaluation set:
- Loss: 0.3605
- Wer: 24.5264
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: 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2223 | 2.35 | 500 | 0.4403 | 37.9922 |
| 0.0908 | 4.69 | 1000 | 0.4041 | 35.6519 |
| 0.0465 | 7.04 | 1500 | 0.4189 | 34.3053 |
| 0.0168 | 9.39 | 2000 | 0.3972 | 29.9127 |
| 0.0118 | 11.74 | 2500 | 0.4043 | 28.9933 |
| 0.0053 | 14.08 | 3000 | 0.3968 | 28.5940 |
| 0.0032 | 16.43 | 3500 | 0.3664 | 25.6779 |
| 0.0009 | 18.78 | 4000 | 0.3665 | 26.2444 |
| 0.0003 | 21.13 | 4500 | 0.3620 | 25.2879 |
| 0.0004 | 23.47 | 5000 | 0.3570 | 24.8607 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2