whisper-medium-21 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - afrispeech-200
metrics:
  - wer
model-index:
  - name: whisper-medium-21
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: afrispeech-200
          type: afrispeech-200
          config: all
          split: train
          args: all
        metrics:
          - name: Wer
            type: wer
            value: 0.1798692249973202

whisper-medium-21

This model is a fine-tuned version of saif-daoud/whisper-medium-20 on the afrispeech-200 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6567
  • Wer: 0.1799

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-06
  • train_batch_size: 8
  • 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: 1500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.3818 0.5 750 0.7995 0.1643
1.1218 1.5 1500 0.6567 0.1799

Framework versions

  • Transformers 4.28.0.dev0
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.2