zuazo/whisper-large-v2-ca

Whisper Large-V2 Catalan

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_13_0 ca dataset. It achieves the following results on the evaluation set:

• Loss: 0.1494
• Wer: 4.6716

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: 32
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 20000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1072	1.02	1000	0.1637	7.0329
0.0239	3.02	2000	0.1784	7.0277
0.0507	5.02	3000	0.1754	6.5773
0.0571	7.02	4000	0.1620	6.5047
0.0193	9.02	5000	0.1821	6.4887
0.0625	11.02	6000	0.1443	6.7585
0.0752	13.02	7000	0.1653	5.9097
0.0359	15.02	8000	0.1406	5.8760
0.0565	17.01	9000	0.1496	5.9680
0.0196	19.01	10000	0.1788	5.2746
0.0215	21.01	11000	0.1539	5.3895
0.0178	23.01	12000	0.1800	5.3764
0.0114	25.01	13000	0.1709	5.2078
0.0123	27.01	14000	0.1827	5.2003
0.0337	29.01	15000	0.1553	5.3655
0.0108	31.01	16000	0.1476	4.9151
0.0194	33.01	17000	0.1396	4.8477
0.0472	35.0	18000	0.1202	4.8717
0.0401	37.0	19000	0.1494	4.6716
0.0127	39.0	20000	0.1187	4.7276

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.