CoolFace
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robello2/whisper-medium-afrispeech-clinical

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face
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Model Card

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whisper-medium-afrispeech-clinical

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

  • Loss: 0.7878
  • Model Preparation Time: 0.0098
  • Wer: 0.136

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
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 2239
  • num_epochs: 10
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossModel Preparation TimeWer
0.49461.022400.55930.00980.157
0.34202.044800.50740.00980.144
0.18563.067200.52420.00980.147
0.11574.089600.56760.00980.142
0.03645.0112000.62160.00980.139
0.01846.0134400.64940.00980.137
0.00667.0156800.69380.00980.137
0.00218.0179200.72830.00980.137
0.00109.0201600.76500.00980.135
0.000610.0224000.78780.00980.136

Framework versions

  • Transformers 5.3.0
  • Pytorch 2.4.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.22.2