metadata
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
Whisper Tiny es
This model is a fine-tuned version of 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:
@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}
}