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Whisper Small Ko(FLUERS) - by p4b

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

  • Loss: 0.4512
  • Wer: 148.1005

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-07
  • train_batch_size: 96
  • eval_batch_size: 64
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000

Training results

Training Loss Epoch Step Validation Loss Wer
0.6003 32.0 800 0.5913 167.2749
0.459 64.0 1600 0.4978 170.9841
0.4035 96.0 2400 0.4653 168.5911
0.3812 128.0 3200 0.4531 149.4765
0.3766 160.0 4000 0.4512 148.1005

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.14.0.dev20221208+cu116
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Evaluation results