whisper-tiny-kor_eng_tiny_ed_ob

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2284
  • Cer: 6.6456

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: 3e-05
  • train_batch_size: 12
  • eval_batch_size: 6
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Cer Validation Loss
0.8207 16.6667 100 6.9620 0.9476
0.0353 33.3333 200 7.9114 0.8010
0.0002 50.0 300 7.9114 0.8538
0.0001 66.6667 400 7.9114 0.8916
0.0 83.3333 500 7.9114 0.9169
0.0 100.0 600 5.9072 0.9309
0.0 116.6667 700 5.8017 0.9514
0.0 133.3333 800 6.1181 0.9646
0.0 150.0 900 6.1181 0.9769
0.0 166.6667 1000 6.1181 0.9847
0.0 183.3333 1100 6.5401 1.0037
0.0 200.0 1200 6.5401 1.0220
0.0 216.6667 1300 6.6456 1.0314
0.0 233.3333 1400 7.1730 1.0465
0.0 250.0 1500 7.1730 1.0657
0.0 266.6667 1600 7.1730 1.0768
0.0 283.3333 1700 7.1730 1.0807
0.0 300.0 1800 7.5949 1.1066
0.0 316.6667 1900 7.5949 1.1196
0.0 333.3333 2000 7.5949 1.1301
0.0 350.0 2100 6.9620 1.1401
0.0 366.6667 2200 6.9620 1.1537
0.0 383.3333 2300 6.9620 1.1606
0.0 400.0 2400 6.9620 1.1631
0.0 416.6667 2500 6.3291 1.1769
0.0 433.3333 2600 6.3291 1.1780
0.0 450.0 2700 7.1730 1.1860
0.0 466.6667 2800 6.0127 1.1920
0.0 483.3333 2900 6.1181 1.1972
0.0 500.0 3000 6.3291 1.2019
0.0 516.6667 3100 6.5401 1.2073
0.0 533.3333 3200 6.7511 1.2118
0.0 550.0 3300 6.6456 1.2163
0.0 566.6667 3400 6.6456 1.2171
0.0 583.3333 3500 6.6456 1.2232
0.0 600.0 3600 1.2269 6.6456
0.0 616.6667 3700 1.2264 6.6456
0.0 633.3333 3800 1.2278 6.6456
0.0 650.0 3900 1.2286 6.6456
0.0 666.6667 4000 1.2284 6.6456

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu126
  • Datasets 3.5.0
  • Tokenizers 0.21.1
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