This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:

Loss: 0.5520
Wer: 25.9772

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: 2.5e-05
train_batch_size: 128
eval_batch_size: 64
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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0174	9.01	1000	0.4597	27.3097
0.0016	19.01	2000	0.5160	26.0197
0.0007	29.0	3000	0.5520	25.9772
0.0005	38.02	4000	0.5728	26.1452
0.0004	48.01	5000	0.5818	26.2202

Framework versions

Transformers 4.33.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3

Citation

If you use these models in your research, please cite:

bibtex

@misc{dezuazo2025whisperlmimprovingasrmodels,
      title={Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languages}, 
      author={Xabier de Zuazo and Eva Navas and Ibon Saratxaga and Inma Hernáez Rioja},
      year={2025},
      eprint={2503.23542},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2503.23542}, 
}

Please, check the related paper preprint in arXiv:2503.23542 for more details.

Licensing

This model is available under the Apache-2.0 License. You are free to use, modify, and distribute this model as long as you credit the original creators.

zuazo/whisper-base-eu

Whisper Base Basque

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Citation

Licensing

zuazo/
whisper-base-eu