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BANG please be the final one (EN)

This model is a fine-tuned version of openai/whisper-large-v3 on the Radio-Modified Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0395
  • Wer: 8.8210

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: 16
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1511 0.25 1000 0.1318 20.4937
0.0685 1.2443 2000 0.0845 12.3199
0.0378 2.2385 3000 0.0557 10.4397
0.0283 3.2328 4000 0.0395 8.8210

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Dataset used to train michaelszhu/whisper-small-finetuned-radio-ASR-2

Evaluation results