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--- |
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language: |
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- ca |
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license: apache-2.0 |
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base_model: openai/whisper-large-v2 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large-V2 Catalan |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: mozilla-foundation/common_voice_13_0 ca |
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type: mozilla-foundation/common_voice_13_0 |
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config: ca |
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split: test |
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args: ca |
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metrics: |
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- name: Wer |
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type: wer |
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value: 4.671620462989425 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Large-V2 Catalan |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_13_0 ca dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1494 |
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- Wer: 4.6716 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 20000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.1072 | 1.02 | 1000 | 0.1637 | 7.0329 | |
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| 0.0239 | 3.02 | 2000 | 0.1784 | 7.0277 | |
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| 0.0507 | 5.02 | 3000 | 0.1754 | 6.5773 | |
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| 0.0571 | 7.02 | 4000 | 0.1620 | 6.5047 | |
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| 0.0193 | 9.02 | 5000 | 0.1821 | 6.4887 | |
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| 0.0625 | 11.02 | 6000 | 0.1443 | 6.7585 | |
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| 0.0752 | 13.02 | 7000 | 0.1653 | 5.9097 | |
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| 0.0359 | 15.02 | 8000 | 0.1406 | 5.8760 | |
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| 0.0565 | 17.01 | 9000 | 0.1496 | 5.9680 | |
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| 0.0196 | 19.01 | 10000 | 0.1788 | 5.2746 | |
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| 0.0215 | 21.01 | 11000 | 0.1539 | 5.3895 | |
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| 0.0178 | 23.01 | 12000 | 0.1800 | 5.3764 | |
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| 0.0114 | 25.01 | 13000 | 0.1709 | 5.2078 | |
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| 0.0123 | 27.01 | 14000 | 0.1827 | 5.2003 | |
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| 0.0337 | 29.01 | 15000 | 0.1553 | 5.3655 | |
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| 0.0108 | 31.01 | 16000 | 0.1476 | 4.9151 | |
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| 0.0194 | 33.01 | 17000 | 0.1396 | 4.8477 | |
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| 0.0472 | 35.0 | 18000 | 0.1202 | 4.8717 | |
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| 0.0401 | 37.0 | 19000 | 0.1494 | 4.6716 | |
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| 0.0127 | 39.0 | 20000 | 0.1187 | 4.7276 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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## Citation |
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If you use these models in your research, please cite: |
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```bibtex |
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@misc{dezuazo2025whisperlmimprovingasrmodels, |
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title={Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languages}, |
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author={Xabier de Zuazo and Eva Navas and Ibon Saratxaga and Inma Hernáez Rioja}, |
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year={2025}, |
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eprint={2503.23542}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2503.23542}, |
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} |
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``` |
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Please, check the related paper preprint in |
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[arXiv:2503.23542](https://arxiv.org/abs/2503.23542) |
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for more details. |
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## Licensing |
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This model is available under the |
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[Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0). |
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You are free to use, modify, and distribute this model as long as you credit |
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the original creators. |
