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---
language:
- eu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Tiny Basque
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 eu
type: mozilla-foundation/common_voice_13_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 32.26943173073028
---
<!-- 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 Tiny Basque
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_13_0 eu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6522
- Wer: 32.2694
## 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: 3.75e-05
- train_batch_size: 256
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0096 | 19.0 | 1000 | 0.5796 | 32.8952 |
| 0.0011 | 38.0 | 2000 | 0.6522 | 32.2694 |
| 0.0005 | 57.01 | 3000 | 0.6949 | 33.1403 |
| 0.0003 | 76.01 | 4000 | 0.7217 | 33.0734 |
| 0.0003 | 96.0 | 5000 | 0.7321 | 33.1585 |
### 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. |