metadata

language:
  - es
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Large-V3 Spanish
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0 es
          type: mozilla-foundation/common_voice_13_0
          config: es
          split: test
          args: es
        metrics:
          - name: Wer
            type: wer
            value: 4.9295277686894154

Whisper Large-V3 Spanish

This model is a fine-tuned version of openai/whisper-large-v3 on the mozilla-foundation/common_voice_13_0 es dataset. It achieves the following results on the evaluation set:

Loss: 0.3245
Wer: 4.9295

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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.058	2.04	1000	0.1540	4.6851
0.0124	4.07	2000	0.1829	4.6787
0.0052	6.11	3000	0.2190	4.8096
0.0024	8.15	4000	0.2289	4.8776
0.0024	10.18	5000	0.2341	4.8923
0.0015	12.22	6000	0.2459	4.9340
0.0021	14.26	7000	0.2558	4.9276
0.0011	16.29	8000	0.2540	5.1015
0.0013	18.33	9000	0.2611	5.1855
0.0005	20.37	10000	0.2720	4.9379
0.0028	22.4	11000	0.2614	5.0110
0.0004	24.44	12000	0.2652	4.9898
0.0004	26.48	13000	0.2850	4.9776
0.0006	28.51	14000	0.2736	4.9732
0.0002	30.55	15000	0.2944	5.1566
0.0002	32.59	16000	0.2949	5.0007
0.0001	34.62	17000	0.3094	4.9552
0.0	36.66	18000	0.3185	4.9622
0.0	38.7	19000	0.3229	4.9462
0.0	40.73	20000	0.3245	4.9295

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1

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.