Whisper Tiny es

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

• deepdml/common_voice_26_0
• disco-eth/WorldSpeech
• facebook/voxpopuli
• facebook/multilingual_librispeech
• deepdml/voxforge
• google/fleurs
• deepdml/basque_parliament_1

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
• 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_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}
    }