Whisper Large-V2 Basque
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.4121
- Wer: 12.6277
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.1098 | 5.85 | 1000 | 0.2495 | 16.6354 |
| 0.022 | 11.7 | 2000 | 0.2733 | 14.6306 |
| 0.0089 | 17.54 | 3000 | 0.3075 | 13.9697 |
| 0.0056 | 23.39 | 4000 | 0.3206 | 14.0724 |
| 0.0053 | 29.24 | 5000 | 0.3314 | 13.7944 |
| 0.0037 | 35.09 | 6000 | 0.3376 | 13.7480 |
| 0.0027 | 40.94 | 7000 | 0.3492 | 13.6815 |
| 0.0023 | 46.78 | 8000 | 0.3455 | 13.8488 |
| 0.002 | 52.63 | 9000 | 0.3500 | 13.5123 |
| 0.0009 | 58.48 | 10000 | 0.3590 | 13.2967 |
| 0.0016 | 64.33 | 11000 | 0.3675 | 13.4679 |
| 0.0007 | 70.18 | 12000 | 0.3785 | 13.2685 |
| 0.0008 | 76.02 | 13000 | 0.3822 | 13.3652 |
| 0.0004 | 81.87 | 14000 | 0.3929 | 13.3148 |
| 0.0006 | 87.72 | 15000 | 0.3880 | 13.1032 |
| 0.0002 | 93.57 | 16000 | 0.4005 | 12.6982 |
| 0.0002 | 99.42 | 17000 | 0.4004 | 13.1516 |
| 0.0001 | 105.26 | 18000 | 0.4140 | 12.8735 |
| 0.0001 | 111.11 | 19000 | 0.4131 | 12.5128 |
| 0.0001 | 116.96 | 20000 | 0.4121 | 12.6277 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1