Whisper
Collection
30 items
•
Updated
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_13_0 ca dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1158 | 1.05 | 1000 | 0.1846 | 8.3630 |
0.0184 | 3.05 | 2000 | 0.2017 | 8.0629 |
0.0522 | 5.04 | 3000 | 0.1940 | 8.1177 |
0.0595 | 7.04 | 4000 | 0.1742 | 7.4696 |
0.0179 | 9.04 | 5000 | 0.1899 | 7.3095 |
0.0646 | 11.04 | 6000 | 0.1555 | 6.3441 |
0.0825 | 13.03 | 7000 | 0.1810 | 6.4841 |
0.0309 | 15.03 | 8000 | 0.1464 | 6.3544 |
0.0695 | 17.03 | 9000 | 0.1434 | 5.9954 |
0.0186 | 19.03 | 10000 | 0.1706 | 6.1097 |
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.
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.
Base model
openai/whisper-medium