whisper-medium-es / README.md
zuazo's picture
Add citation and licensing
5382ed3 verified
metadata
language:
  - es
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Medium Spanish
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0 es
          type: mozilla-foundation/common_voice_13_0
          config: es
          split: test
          args: es
        metrics:
          - name: Wer
            type: wer
            value: 5.408751772230669

Whisper Medium Spanish

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

  • Loss: 0.1915
  • Wer: 5.4088

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
0.0917 2.0 1000 0.1944 6.8560
0.0927 4.0 2000 0.1817 6.1439
0.0456 6.01 3000 0.1805 6.2626
0.0343 8.01 4000 0.2097 6.1773
0.0046 10.01 5000 0.2292 5.9374
0.0829 12.01 6000 0.1814 6.0644
0.0021 14.01 7000 0.2318 5.7096
0.0288 16.01 8000 0.1871 5.5755
0.1297 18.02 9000 0.1831 5.6885
0.0377 20.02 10000 0.1915 5.4088

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.