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metadata
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Medium Galician
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs gl_es
          type: google/fleurs
          config: gl_es
          split: test
          args: gl_es
        metrics:
          - name: Wer
            type: wer
            value: 14.674060048688126

Whisper Medium Galician

This model is a fine-tuned version of openai/whisper-medium on the google/fleurs gl_es dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4553
  • Wer: 14.6741

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: 32
  • eval_batch_size: 32
  • 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
0.0002 39.01 1000 0.4553 14.6741
0.0001 79.0 2000 0.5023 14.9400
0.0 119.0 3000 0.5317 15.1609
0.0 159.0 4000 0.5513 15.2015
0.0 199.0 5000 0.5593 15.2060

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2