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metadata
language:
  - ko
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper_medium
    results: []

whisper_medium

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

  • Loss: 1.6505
  • Cer: 12.0457
  • Wer: 29.9853

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: 4
  • eval_batch_size: 4
  • 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: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Wer
1.6678 0.04 500 1.6505 12.0457 29.9853

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.15.0
  • Tokenizers 0.15.0