README.md

metadata

language:
  - es
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
base_model: openai/whisper-small
datasets:
  - mozilla-foundation/common_voice_17_0
  - google/fleurs
  - facebook/multilingual_librispeech
  - facebook/voxpopuli
metrics:
  - wer
model-index:
  - name: Whisper Small Mixed-Spanish
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_17_0 es
          type: mozilla-foundation/common_voice_17_0
          config: es
          split: test
          args: es
        metrics:
          - type: wer
            value: 8.634474343167287
            name: Wer
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: es_419
          split: test
        metrics:
          - type: wer
            value: 5.34
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: facebook/multilingual_librispeech
          type: facebook/multilingual_librispeech
          config: spanish
          split: test
        metrics:
          - type: wer
            value: 6.02
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: facebook/voxpopuli
          type: facebook/voxpopuli
          config: es
          split: test
        metrics:
          - type: wer
            value: 8.55
            name: WER
pipeline_tag: automatic-speech-recognition

Whisper Small Mixed-Spanish

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

• mozilla-foundation/common_voice_17_0
• google/fleurs
• facebook/multilingual_librispeech
• facebook/voxpopuli

It achieves the following results on the evaluation set:

• Loss: 0.1809
• Wer: 8.6345

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: 64
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.247	0.2	1000	0.2160	10.3975
0.1337	0.4	2000	0.2010	9.6749
0.1401	0.6	3000	0.1905	9.0946
0.1714	0.8	4000	0.1849	8.8550
0.1046	1.0	5000	0.1809	8.6345

Framework versions

• Transformers 4.42.0.dev0
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1