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openai/whisper-large-v2

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2352
  • Wer: 8.1166
  • Cer: 5.0032

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.0897 0.1 1000 0.1884 11.0068 6.6992
0.0396 0.2 2000 0.1749 9.7399 5.9350
0.036 1.1 3000 0.1698 9.1419 5.6781
0.012 1.2 4000 0.1849 9.3041 5.7661
0.0151 2.09 5000 0.1879 9.1959 5.6761
0.0047 2.19 6000 0.2097 8.6706 5.4422
0.0046 3.09 7000 0.2040 8.8277 5.4717
0.0015 3.19 8000 0.2260 8.4949 5.3101
0.0013 4.09 9000 0.2339 8.3716 5.1471
0.0005 4.19 10000 0.2352 8.1166 5.0032

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train vumichien/whisper-large-v2-jp

Evaluation results