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audiotranscribe

Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-medium-medical
    results: []

whisper-medium-medical

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

  • Loss: 0.0562
  • Wer: 10.7169

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: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.5008 0.5405 100 0.1965 12.0203
0.1034 1.0811 200 0.0870 12.2616
0.0563 1.6216 300 0.0642 8.3514
0.0238 2.1622 400 0.0610 11.6341
0.0129 2.7027 500 0.0562 10.7169

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.6.0+cu118
  • Datasets 3.3.1
  • Tokenizers 0.21.0