Whisper Small En - Moh

This model is a fine-tuned version of openai/whisper-small on the AfriSpeech dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6236
  • Wer: 32.8714

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: 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: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.677 0.5 500 0.6841 31.2466
0.428 1.0 1000 0.6236 32.8714

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Dataset used to train MohDz/dsn_afrispeech_small

Evaluation results