deepdml/whisper-tiny-es-mix-norm

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Whisper Tiny es

This model is a fine-tuned version of openai/whisper-tiny on the following datasets:

• —deepdml/commonvoice26_0
• —disco-eth/WorldSpeech
• —facebook/voxpopuli
• —facebook/multilingual_librispeech
• —deepdml/voxforge
• —google/fleurs
• —deepdml/basqueparliament1

It achieves the following results on the evaluation set:

• —Best checkpoint: 44,000
• —Loss: 0.2888
• —Wer: 16.0693
• —Cer: 6.0413

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
• —trainbatchsize: 128
• —evalbatchsize: 128
• —seed: 42
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 0.04
• —training_steps: 46000

Training results

Framework versions

• —Transformers 5.14.1
• —Pytorch 2.6.0+cu124
• —Datasets 5.0.1
• —Tokenizers 0.22.2

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}
    }