128 lines
3.8 KiB
Markdown
128 lines
3.8 KiB
Markdown
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---
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language:
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- es
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license: apache-2.0
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base_model: openai/whisper-large-v3
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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-V3 Spanish
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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 es
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type: mozilla-foundation/common_voice_13_0
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config: es
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split: test
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args: es
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metrics:
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- name: Wer
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type: wer
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value: 4.9295277686894154
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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-V3 Spanish
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_13_0 es dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3245
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- Wer: 4.9295
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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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- mixed_precision_training: Native AMP
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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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| 0.058 | 2.04 | 1000 | 0.1540 | 4.6851 |
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| 0.0124 | 4.07 | 2000 | 0.1829 | 4.6787 |
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| 0.0052 | 6.11 | 3000 | 0.2190 | 4.8096 |
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| 0.0024 | 8.15 | 4000 | 0.2289 | 4.8776 |
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| 0.0024 | 10.18 | 5000 | 0.2341 | 4.8923 |
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| 0.0015 | 12.22 | 6000 | 0.2459 | 4.9340 |
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| 0.0021 | 14.26 | 7000 | 0.2558 | 4.9276 |
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| 0.0011 | 16.29 | 8000 | 0.2540 | 5.1015 |
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| 0.0013 | 18.33 | 9000 | 0.2611 | 5.1855 |
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| 0.0005 | 20.37 | 10000 | 0.2720 | 4.9379 |
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| 0.0028 | 22.4 | 11000 | 0.2614 | 5.0110 |
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| 0.0004 | 24.44 | 12000 | 0.2652 | 4.9898 |
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| 0.0004 | 26.48 | 13000 | 0.2850 | 4.9776 |
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| 0.0006 | 28.51 | 14000 | 0.2736 | 4.9732 |
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| 0.0002 | 30.55 | 15000 | 0.2944 | 5.1566 |
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| 0.0002 | 32.59 | 16000 | 0.2949 | 5.0007 |
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| 0.0001 | 34.62 | 17000 | 0.3094 | 4.9552 |
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| 0.0 | 36.66 | 18000 | 0.3185 | 4.9622 |
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| 0.0 | 38.7 | 19000 | 0.3229 | 4.9462 |
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| 0.0 | 40.73 | 20000 | 0.3245 | 4.9295 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.2.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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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.
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