zuazo/whisper-medium-eu

Whisper Medium Basque

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

• Loss: 0.4119
• Wer: 14.1196

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: 64
• eval_batch_size: 32
• 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: 10000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0206	4.02	1000	0.2998	16.9995
0.0036	9.01	2000	0.3235	15.5211
0.0018	14.01	3000	0.3454	14.9905
0.0013	19.01	4000	0.3538	14.9439
0.0013	24.01	5000	0.3587	14.8568
0.0002	29.0	6000	0.3799	14.4153
0.0001	33.02	7000	0.3937	14.2067
0.0001	38.02	8000	0.4050	14.1946
0.0001	43.01	9000	0.4119	14.1196
0.0001	48.01	10000	0.4150	14.1358

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:

@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.