| --- |
| library_name: transformers |
| language: |
| - es |
| license: apache-2.0 |
| base_model: openai/whisper-tiny |
| tags: |
| - generated_from_trainer |
| datasets: |
| - deepdml/voxforge |
| - fixie-ai/common_voice_17_0 |
| - google/fleurs |
| - deepdml/basque_parliament_1 |
| - facebook/multilingual_librispeech |
| - facebook/voxpopuli |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Tiny es |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 17.0 |
| type: deepdml/voxforge |
| metrics: |
| - name: Wer |
| type: wer |
| value: 21.674748489027575 |
| --- |
| <!-- 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 es |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3749 |
| - Wer Raw: 21.6741 |
| - Cer Raw: 8.4585 |
| - Wer: 21.6747 |
| - Cer: 8.4585 |
|
|
| ## 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: 128 |
| - eval_batch_size: 128 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.04 |
| - training_steps: 20000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer Raw | Cer Raw | Wer | Cer | |
| |:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:| |
| | 0.3891 | 0.05 | 1000 | 0.6939 | 37.6291 | 14.8103 | 37.4810 | 14.7830 | |
| | 0.6597 | 0.1 | 2000 | 0.6883 | 34.8302 | 14.4460 | 34.8016 | 14.4405 | |
| | 0.1388 | 0.15 | 3000 | 0.6530 | 34.3358 | 13.1348 | 34.2976 | 13.1269 | |
| | 0.1217 | 0.2 | 4000 | 0.6682 | 34.5982 | 13.2295 | 34.5646 | 13.2233 | |
| | 0.1101 | 0.25 | 5000 | 0.6721 | 35.2325 | 13.7696 | 35.1969 | 13.7628 | |
| | 0.3564 | 0.3 | 6000 | 0.5374 | 28.6885 | 11.2075 | 28.6529 | 11.2010 | |
| | 0.3803 | 0.35 | 7000 | 0.3890 | 20.9394 | 7.6348 | 20.9369 | 7.6342 | |
| | 0.3373 | 0.4 | 8000 | 0.3540 | 19.9264 | 7.3914 | 19.9258 | 7.3913 | |
| | 0.2828 | 1.0134 | 9000 | 0.3343 | 18.6452 | 6.8455 | 18.6452 | 6.8455 | |
| | 0.2743 | 1.0634 | 10000 | 0.3218 | 17.8476 | 6.5983 | 17.8476 | 6.5983 | |
| | 0.2747 | 1.1134 | 11000 | 0.3123 | 17.2210 | 6.3677 | 17.2210 | 6.3677 | |
| | 0.116 | 1.1634 | 12000 | 0.3392 | 19.6398 | 7.3330 | 19.6398 | 7.3330 | |
| | 0.1081 | 1.2134 | 13000 | 0.3717 | 22.2626 | 8.5878 | 22.2626 | 8.5878 | |
| | 0.0918 | 1.2634 | 14000 | 0.3865 | 22.8498 | 8.6366 | 22.8498 | 8.6366 | |
| | 0.0908 | 1.3134 | 15000 | 0.3957 | 23.3710 | 8.8869 | 23.3710 | 8.8869 | |
| | 0.493 | 1.3634 | 16000 | 0.4018 | 22.0878 | 8.2129 | 22.0878 | 8.2129 | |
| | 0.4284 | 1.4134 | 17000 | 0.3943 | 22.6592 | 8.8754 | 22.6592 | 8.8754 | |
| | 0.3042 | 2.0268 | 18000 | 0.3967 | 22.3014 | 8.5581 | 22.3014 | 8.5581 | |
| | 0.2942 | 2.0768 | 19000 | 0.3946 | 22.5136 | 8.8319 | 22.5136 | 8.8319 | |
| | 0.1001 | 2.1268 | 20000 | 0.3749 | 21.6741 | 8.4585 | 21.6747 | 8.4585 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.0.dev0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.0 |
| |
| ## Citation |
| |
| Please cite the model using the following BibTeX entry: |
| |
| ```bibtex |
| @misc{deepdml/whisper-tiny-es-mix-norm, |
| title={Fine-tuned Whisper tiny ASR model for speech recognition in Spanish}, |
| author={Jimenez, David}, |
| howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-es-mix-norm}}, |
| year={2026} |
| } |
| ``` |
| |
