Whisper Large-V2 Basque
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_16_1 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.4206
- Wer: 7.7204
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: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 40000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0112 | 10.04 | 1000 | 0.2182 | 10.1571 |
| 0.0052 | 20.08 | 2000 | 0.2372 | 9.6276 |
| 0.0017 | 30.11 | 3000 | 0.2417 | 9.0150 |
| 0.0022 | 40.15 | 4000 | 0.2341 | 8.8938 |
| 0.0023 | 50.19 | 5000 | 0.2451 | 8.9388 |
| 0.0006 | 60.23 | 6000 | 0.2517 | 8.4161 |
| 0.0006 | 70.26 | 7000 | 0.2499 | 8.0985 |
| 0.0008 | 80.3 | 8000 | 0.2548 | 8.3467 |
| 0.0004 | 90.34 | 9000 | 0.2498 | 7.9559 |
| 0.0003 | 100.38 | 10000 | 0.2489 | 7.6940 |
| 0.0 | 110.41 | 11000 | 0.2906 | 7.5455 |
| 0.0 | 120.45 | 12000 | 0.3027 | 7.4596 |
| 0.0 | 130.49 | 13000 | 0.3137 | 7.4517 |
| 0.0 | 140.53 | 14000 | 0.3243 | 7.4644 |
| 0.0 | 150.56 | 15000 | 0.3351 | 7.4762 |
| 0.0 | 160.6 | 16000 | 0.3459 | 7.4556 |
| 0.0 | 170.64 | 17000 | 0.3565 | 7.4605 |
| 0.0 | 180.68 | 18000 | 0.3689 | 7.4996 |
| 0.0 | 190.72 | 19000 | 0.3806 | 7.5934 |
| 0.0 | 200.75 | 20000 | 0.3912 | 7.6344 |
| 0.0 | 210.79 | 21000 | 0.4005 | 7.5485 |
| 0.0 | 220.83 | 22000 | 0.4102 | 7.6266 |
| 0.0079 | 230.87 | 23000 | 0.2467 | 9.1654 |
| 0.0 | 240.9 | 24000 | 0.3097 | 7.7615 |
| 0.0 | 250.94 | 25000 | 0.3311 | 7.7243 |
| 0.0 | 260.98 | 26000 | 0.3446 | 7.7028 |
| 0.0 | 271.02 | 27000 | 0.3551 | 7.7546 |
| 0.0 | 281.05 | 28000 | 0.3646 | 7.7986 |
| 0.0 | 291.09 | 29000 | 0.3729 | 7.7781 |
| 0.0 | 301.13 | 30000 | 0.3811 | 7.7634 |
| 0.0 | 311.17 | 31000 | 0.3878 | 7.7702 |
| 0.0 | 321.2 | 32000 | 0.3948 | 7.7722 |
| 0.0 | 331.24 | 33000 | 0.4003 | 7.7302 |
| 0.0 | 341.28 | 34000 | 0.4058 | 7.7312 |
| 0.0 | 351.32 | 35000 | 0.4108 | 7.7292 |
| 0.0 | 361.36 | 36000 | 0.4142 | 7.7321 |
| 0.0 | 371.39 | 37000 | 0.4170 | 7.7204 |
| 0.0 | 381.43 | 38000 | 0.4189 | 7.7253 |
| 0.0 | 391.47 | 39000 | 0.4202 | 7.7263 |
| 0.0 | 401.51 | 40000 | 0.4206 | 7.7204 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1