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whisper_hyojin2

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Korean
whisper
hf-asr-leaderboard
Generated from Trainer
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whisper_hyojin2 / README.md
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metadata
language:
  - ko
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - hyojin99/EBRC
base_model: openai/whisper-base
model-index:
  - name: ft_model
    results: []

ft_model

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

  • Loss: 0.4044
  • Cer: 16.1170

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: 6250
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
0.4709 1.0 1250 0.4644 20.4829
0.2318 2.0 2500 0.3985 17.9464
0.1339 3.0 3750 0.3915 16.9433
0.0539 4.0 5000 0.3962 16.2937
0.0206 5.0 6250 0.4044 16.1170

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2