tuning_test / README.md
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metadata
language:
  - ko
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
base_model: openai/whisper-base
datasets:
  - Drunk/aihub_sample
model-index:
  - name: tuning_test_whisper
    results: []

Visualize in Weights & Biases

tuning_test_whisper

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

  • Loss: 1.2301
  • Cer: 18.4549

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: 16
  • eval_batch_size: 8
  • 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: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
0.0001 500.0 1000 1.0798 18.0258
0.0001 1000.0 2000 1.1747 18.4549
0.0 1500.0 3000 1.2109 18.4549
0.0 2000.0 4000 1.2301 18.4549

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 1.13.1+cu116
  • Datasets 2.19.1
  • Tokenizers 0.19.1