---
language:
- gl
license: apache-2.0
base_model: openai/whisper-large
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large Galician
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 gl
      type: mozilla-foundation/common_voice_13_0
      config: gl
      split: test
      args: gl
    metrics:
    - name: Wer
      type: wer
      value: 6.939845474613686
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Large Galician

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_13_0 gl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3605
- Wer: 6.9398

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0126        | 4.01  | 1000  | 0.2128          | 8.3558 |
| 0.0032        | 9.01  | 2000  | 0.2262          | 6.9416 |
| 0.0022        | 14.01 | 3000  | 0.2528          | 7.1123 |
| 0.0025        | 19.01 | 4000  | 0.2643          | 7.3641 |
| 0.0015        | 24.01 | 5000  | 0.2596          | 7.3365 |
| 0.0014        | 29.01 | 6000  | 0.2723          | 7.6366 |
| 0.0008        | 34.01 | 7000  | 0.2778          | 7.6090 |
| 0.0003        | 39.01 | 8000  | 0.2880          | 7.2261 |
| 0.0004        | 44.01 | 9000  | 0.2920          | 7.6745 |
| 0.0001        | 49.01 | 10000 | 0.2854          | 7.4089 |
| 0.0           | 54.01 | 11000 | 0.3027          | 7.4365 |
| 0.0           | 59.01 | 12000 | 0.3159          | 7.4055 |
| 0.0           | 64.01 | 13000 | 0.3242          | 7.3693 |
| 0.0           | 69.01 | 14000 | 0.3312          | 7.3072 |
| 0.0           | 74.01 | 15000 | 0.3379          | 7.0226 |
| 0.0           | 79.01 | 16000 | 0.3442          | 7.0019 |
| 0.0           | 84.01 | 17000 | 0.3500          | 6.9933 |
| 0.0           | 89.01 | 18000 | 0.3550          | 6.9605 |
| 0.0           | 94.01 | 19000 | 0.3589          | 6.9467 |
| 0.0           | 99.01 | 20000 | 0.3605          | 6.9398 |


### 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:

```bibtex
@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](https://arxiv.org/abs/2503.23542)
for more details.

## Licensing

This model is available under the
[Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
You are free to use, modify, and distribute this model as long as you credit
the original creators.