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whisper_large

Automatic Speech Recognition
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whisper
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metadata
language:
  - ko
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
base_model: openai/whisper-small
datasets:
  - hyojin99/EBRC
model-index:
  - name: ft_model
    results: []

ft_model

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

  • Loss: 0.2978
  • Cer: 10.5708

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 6000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
0.3829 1.0 1500 0.3817 15.4574
0.1779 2.0 3000 0.3238 13.5614
0.0732 3.0 4500 0.2954 11.2004
0.0228 4.0 6000 0.2978 10.5708

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1