Whisper Large-V3 Basque
This model is a fine-tuned version of openai/whisper-large-v3 on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.4180
- Wer: 13.2886
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 |
|---|---|---|---|---|
| 0.1288 | 5.85 | 1000 | 0.2746 | 18.6000 |
| 0.0262 | 11.7 | 2000 | 0.2894 | 16.0934 |
| 0.0095 | 17.54 | 3000 | 0.3281 | 15.7348 |
| 0.0056 | 23.39 | 4000 | 0.3362 | 14.7394 |
| 0.0045 | 29.24 | 5000 | 0.3465 | 14.9912 |
| 0.0032 | 35.09 | 6000 | 0.3599 | 14.7172 |
| 0.002 | 40.94 | 7000 | 0.3624 | 14.4150 |
| 0.0028 | 46.78 | 8000 | 0.3647 | 14.4553 |
| 0.0019 | 52.63 | 9000 | 0.3726 | 14.4210 |
| 0.0011 | 58.48 | 10000 | 0.3784 | 14.1268 |
| 0.0011 | 64.33 | 11000 | 0.3753 | 14.2517 |
| 0.0009 | 70.18 | 12000 | 0.3845 | 13.9193 |
| 0.0008 | 76.02 | 13000 | 0.3910 | 14.0402 |
| 0.0008 | 81.87 | 14000 | 0.3988 | 13.8488 |
| 0.0004 | 87.72 | 15000 | 0.4002 | 13.5788 |
| 0.0002 | 93.57 | 16000 | 0.4021 | 13.5526 |
| 0.0002 | 99.42 | 17000 | 0.4121 | 13.5747 |
| 0.0002 | 105.26 | 18000 | 0.4178 | 13.5989 |
| 0.0005 | 111.11 | 19000 | 0.4135 | 13.3551 |
| 0.0001 | 116.96 | 20000 | 0.4180 | 13.2886 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1