Whisper Base Basque
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_17_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.4594
- Wer: 13.3167
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: 3.75e-05
- train_batch_size: 128
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.0638 | 4.6948 | 1000 | 0.2553 | 17.4365 |
| 0.0058 | 9.3897 | 2000 | 0.2922 | 16.3024 |
| 0.0063 | 14.0845 | 3000 | 0.3181 | 16.5021 |
| 0.0047 | 18.7793 | 4000 | 0.3290 | 16.3152 |
| 0.0038 | 23.4742 | 5000 | 0.3358 | 15.9698 |
| 0.002 | 28.1690 | 6000 | 0.3449 | 15.7408 |
| 0.0028 | 32.8638 | 7000 | 0.3470 | 15.6089 |
| 0.0015 | 37.5587 | 8000 | 0.3582 | 15.5576 |
| 0.0019 | 42.2535 | 9000 | 0.3658 | 15.3157 |
| 0.0013 | 46.9484 | 10000 | 0.3606 | 15.0619 |
| 0.0018 | 51.6432 | 11000 | 0.3786 | 15.2415 |
| 0.0008 | 56.3380 | 12000 | 0.3760 | 15.0867 |
| 0.0016 | 61.0329 | 13000 | 0.3736 | 15.1114 |
| 0.0005 | 65.7277 | 14000 | 0.3750 | 14.5022 |
| 0.0019 | 70.4225 | 15000 | 0.3899 | 15.2433 |
| 0.0005 | 75.1174 | 16000 | 0.3851 | 15.0207 |
| 0.0007 | 79.8122 | 17000 | 0.3922 | 14.8613 |
| 0.0003 | 84.5070 | 18000 | 0.3889 | 14.4628 |
| 0.0 | 89.2019 | 19000 | 0.3941 | 14.0056 |
| 0.0 | 93.8967 | 20000 | 0.4005 | 13.8591 |
| 0.0 | 98.5915 | 21000 | 0.4057 | 13.7097 |
| 0.0 | 103.2864 | 22000 | 0.4110 | 13.6044 |
| 0.0 | 107.9812 | 23000 | 0.4165 | 13.5274 |
| 0.0 | 112.6761 | 24000 | 0.4225 | 13.4871 |
| 0.0 | 117.3709 | 25000 | 0.4290 | 13.4120 |
| 0.0 | 122.0657 | 26000 | 0.4361 | 13.4633 |
| 0.0 | 126.7606 | 27000 | 0.4438 | 13.4358 |
| 0.0 | 131.4554 | 28000 | 0.4515 | 13.3506 |
| 0.0 | 136.1502 | 29000 | 0.4594 | 13.3167 |
| 0.0 | 140.8451 | 30000 | 0.4672 | 13.4386 |
| 0.0 | 145.5399 | 31000 | 0.4750 | 13.4441 |
| 0.0 | 150.2347 | 32000 | 0.4827 | 13.4248 |
| 0.0 | 154.9296 | 33000 | 0.4891 | 13.4294 |
| 0.0 | 159.6244 | 34000 | 0.4952 | 13.4221 |
| 0.0 | 164.3192 | 35000 | 0.5003 | 13.3634 |
| 0.0 | 169.0141 | 36000 | 0.5041 | 13.3561 |
| 0.0 | 173.7089 | 37000 | 0.5069 | 13.3579 |
| 0.0 | 178.4038 | 38000 | 0.5091 | 13.3479 |
| 0.0 | 183.0986 | 39000 | 0.5103 | 13.3396 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1