--- library_name: peft language: - ko license: mit base_model: openai/whisper-large-v3-turbo tags: - generated_from_trainer model-index: - name: Whisper Small ko results: [] --- # Whisper Small ko This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the custom dataset. It achieves the following results on the evaluation set: - Loss: 0.0681 ## 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: 0.001 - train_batch_size: 64 - eval_batch_size: 256 - 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: 200 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.7511 | 0.0641 | 10 | 1.4828 | | 0.6562 | 0.1282 | 20 | 1.2493 | | 0.3357 | 0.1923 | 30 | 0.8826 | | 0.1966 | 0.2564 | 40 | 0.7550 | | 0.1566 | 0.3205 | 50 | 0.6223 | | 0.1253 | 0.3846 | 60 | 0.5636 | | 0.104 | 0.4487 | 70 | 0.5163 | | 0.0979 | 0.5128 | 80 | 0.4967 | | 0.0913 | 0.5769 | 90 | 0.4598 | | 0.107 | 0.6410 | 100 | 0.4358 | | 0.1104 | 0.7051 | 110 | 0.4337 | | 0.0819 | 0.7692 | 120 | 0.4072 | | 0.0892 | 0.8333 | 130 | 0.3902 | | 0.0954 | 0.8974 | 140 | 0.3555 | | 0.0789 | 0.9615 | 150 | 0.3516 | | 0.0811 | 1.0256 | 160 | 0.3237 | | 0.0822 | 1.0897 | 170 | 0.2995 | | 0.0747 | 1.1538 | 180 | 0.3195 | | 0.0838 | 1.2179 | 190 | 0.3436 | | 0.0587 | 1.2821 | 200 | 0.3178 | | 0.0675 | 1.3462 | 210 | 0.2981 | | 0.062 | 1.4103 | 220 | 0.2745 | | 0.0662 | 1.4744 | 230 | 0.2650 | | 0.0639 | 1.5385 | 240 | 0.2802 | | 0.0745 | 1.6026 | 250 | 0.3079 | | 0.0632 | 1.6667 | 260 | 0.2631 | | 0.0724 | 1.7308 | 270 | 0.2406 | | 0.0728 | 1.7949 | 280 | 0.2496 | | 0.0601 | 1.8590 | 290 | 0.2328 | | 0.0653 | 1.9231 | 300 | 0.2230 | | 0.0668 | 1.9872 | 310 | 0.2076 | | 0.0606 | 2.0513 | 320 | 0.1849 | | 0.0543 | 2.1154 | 330 | 0.1851 | | 0.0493 | 2.1795 | 340 | 0.1697 | | 0.047 | 2.2436 | 350 | 0.1630 | | 0.0451 | 2.3077 | 360 | 0.1647 | | 0.0403 | 2.3718 | 370 | 0.1634 | | 0.0477 | 2.4359 | 380 | 0.1530 | | 0.0491 | 2.5 | 390 | 0.1517 | | 0.0444 | 2.5641 | 400 | 0.1464 | | 0.0399 | 2.6282 | 410 | 0.1421 | | 0.0622 | 2.6923 | 420 | 0.1690 | | 0.0509 | 2.7564 | 430 | 0.1800 | | 0.0447 | 2.8205 | 440 | 0.1773 | | 0.0496 | 2.8846 | 450 | 0.1765 | | 0.049 | 2.9487 | 460 | 0.1721 | | 0.0388 | 3.0128 | 470 | 0.1666 | | 0.0667 | 3.0769 | 480 | 0.1477 | | 0.038 | 3.1410 | 490 | 0.1378 | | 0.0363 | 3.2051 | 500 | 0.1376 | | 0.0264 | 3.2692 | 510 | 0.1289 | | 0.032 | 3.3333 | 520 | 0.1339 | | 0.0324 | 3.3974 | 530 | 0.1226 | | 0.034 | 3.4615 | 540 | 0.1196 | | 0.0257 | 3.5256 | 550 | 0.1092 | | 0.0355 | 3.5897 | 560 | 0.1054 | | 0.0256 | 3.6538 | 570 | 0.1096 | | 0.033 | 3.7179 | 580 | 0.1063 | | 0.0337 | 3.7821 | 590 | 0.1121 | | 0.0324 | 3.8462 | 600 | 0.1065 | | 0.0327 | 3.9103 | 610 | 0.1075 | | 0.0314 | 3.9744 | 620 | 0.1042 | | 0.0407 | 4.0385 | 630 | 0.0929 | | 0.0185 | 4.1026 | 640 | 0.1295 | | 0.0215 | 4.1667 | 650 | 0.1258 | | 0.0198 | 4.2308 | 660 | 0.1269 | | 0.0204 | 4.2949 | 670 | 0.1243 | | 0.019 | 4.3590 | 680 | 0.1252 | | 0.0236 | 4.4231 | 690 | 0.1229 | | 0.0263 | 4.4872 | 700 | 0.1196 | | 0.0232 | 4.5513 | 710 | 0.1184 | | 0.0189 | 4.6154 | 720 | 0.1171 | | 0.0187 | 4.6795 | 730 | 0.1155 | | 0.0199 | 4.7436 | 740 | 0.1114 | | 0.026 | 4.8077 | 750 | 0.1105 | | 0.0193 | 4.8718 | 760 | 0.1112 | | 0.0174 | 4.9359 | 770 | 0.1116 | | 0.0205 | 5.0 | 780 | 0.1117 | | 0.0132 | 5.0641 | 790 | 0.1101 | | 0.0125 | 5.1282 | 800 | 0.1100 | | 0.0142 | 5.1923 | 810 | 0.1098 | | 0.0555 | 5.2564 | 820 | 0.0805 | | 0.0138 | 5.3205 | 830 | 0.0787 | | 0.0193 | 5.3846 | 840 | 0.0748 | | 0.0141 | 5.4487 | 850 | 0.0731 | | 0.0158 | 5.5128 | 860 | 0.0724 | | 0.0133 | 5.5769 | 870 | 0.0722 | | 0.0166 | 5.6410 | 880 | 0.0716 | | 0.0125 | 5.7051 | 890 | 0.0706 | | 0.0133 | 5.7692 | 900 | 0.0701 | | 0.0209 | 5.8333 | 910 | 0.0700 | | 0.0144 | 5.8974 | 920 | 0.0696 | | 0.0111 | 5.9615 | 930 | 0.0697 | | 0.0109 | 6.0256 | 940 | 0.0691 | | 0.0131 | 6.0897 | 950 | 0.0688 | | 0.0174 | 6.1538 | 960 | 0.0685 | | 0.0094 | 6.2179 | 970 | 0.0684 | | 0.0128 | 6.2821 | 980 | 0.0682 | | 0.011 | 6.3462 | 990 | 0.0681 | | 0.0112 | 6.4103 | 1000 | 0.0681 | ### Framework versions - PEFT 0.14.0 - Transformers 4.47.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0