--- 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: 0.3628 ## 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: 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: 100 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.9038 | 0.0813 | 10 | 1.5912 | | 0.9253 | 0.1626 | 20 | 1.5826 | | 0.8846 | 0.2439 | 30 | 1.5672 | | 0.8716 | 0.3252 | 40 | 1.5414 | | 0.8208 | 0.4065 | 50 | 1.4999 | | 0.7729 | 0.4878 | 60 | 1.4312 | | 0.6709 | 0.5691 | 70 | 1.3037 | | 0.4743 | 0.6504 | 80 | 1.0660 | | 0.3255 | 0.7317 | 90 | 0.9261 | | 0.2445 | 0.8130 | 100 | 0.8726 | | 0.2058 | 0.8943 | 110 | 0.8373 | | 0.1868 | 0.9756 | 120 | 0.8078 | | 0.1693 | 1.0569 | 130 | 0.7770 | | 0.149 | 1.1382 | 140 | 0.7423 | | 0.1342 | 1.2195 | 150 | 0.7108 | | 0.1379 | 1.3008 | 160 | 0.6793 | | 0.1062 | 1.3821 | 170 | 0.6545 | | 0.1105 | 1.4634 | 180 | 0.6406 | | 0.0938 | 1.5447 | 190 | 0.6334 | | 0.1214 | 1.6260 | 200 | 0.6210 | | 0.0894 | 1.7073 | 210 | 0.6023 | | 0.0806 | 1.7886 | 220 | 0.5867 | | 0.0705 | 1.8699 | 230 | 0.5730 | | 0.0768 | 1.9512 | 240 | 0.5677 | | 0.0671 | 2.0325 | 250 | 0.5617 | | 0.0782 | 2.1138 | 260 | 0.5549 | | 0.0919 | 2.1951 | 270 | 0.5433 | | 0.0689 | 2.2764 | 280 | 0.5278 | | 0.0763 | 2.3577 | 290 | 0.5220 | | 0.0651 | 2.4390 | 300 | 0.5192 | | 0.0601 | 2.5203 | 310 | 0.5108 | | 0.0638 | 2.6016 | 320 | 0.5039 | | 0.0596 | 2.6829 | 330 | 0.4954 | | 0.0635 | 2.7642 | 340 | 0.4901 | | 0.0604 | 2.8455 | 350 | 0.4882 | | 0.0473 | 2.9268 | 360 | 0.4868 | | 0.0601 | 3.0081 | 370 | 0.4845 | | 0.0513 | 3.0894 | 380 | 0.4780 | | 0.0608 | 3.1707 | 390 | 0.4723 | | 0.0593 | 3.2520 | 400 | 0.4678 | | 0.0508 | 3.3333 | 410 | 0.4644 | | 0.0476 | 3.4146 | 420 | 0.4605 | | 0.0629 | 3.4959 | 430 | 0.4584 | | 0.0467 | 3.5772 | 440 | 0.4551 | | 0.0718 | 3.6585 | 450 | 0.4462 | | 0.0496 | 3.7398 | 460 | 0.4392 | | 0.0477 | 3.8211 | 470 | 0.4371 | | 0.0461 | 3.9024 | 480 | 0.4348 | | 0.0464 | 3.9837 | 490 | 0.4320 | | 0.0571 | 4.0650 | 500 | 0.4299 | | 0.0446 | 4.1463 | 510 | 0.4271 | | 0.0435 | 4.2276 | 520 | 0.4253 | | 0.0461 | 4.3089 | 530 | 0.4242 | | 0.0467 | 4.3902 | 540 | 0.4222 | | 0.0499 | 4.4715 | 550 | 0.4200 | | 0.0607 | 4.5528 | 560 | 0.4162 | | 0.0435 | 4.6341 | 570 | 0.4097 | | 0.0463 | 4.7154 | 580 | 0.4047 | | 0.0382 | 4.7967 | 590 | 0.4021 | | 0.0452 | 4.8780 | 600 | 0.4013 | | 0.0447 | 4.9593 | 610 | 0.4007 | | 0.0478 | 5.0407 | 620 | 0.3992 | | 0.0411 | 5.1220 | 630 | 0.3983 | | 0.0429 | 5.2033 | 640 | 0.3959 | | 0.0384 | 5.2846 | 650 | 0.3959 | | 0.0377 | 5.3659 | 660 | 0.3944 | | 0.0443 | 5.4472 | 670 | 0.3907 | | 0.0366 | 5.5285 | 680 | 0.3893 | | 0.0413 | 5.6098 | 690 | 0.3883 | | 0.0439 | 5.6911 | 700 | 0.3877 | | 0.0441 | 5.7724 | 710 | 0.3868 | | 0.0371 | 5.8537 | 720 | 0.3851 | | 0.0461 | 5.9350 | 730 | 0.3837 | | 0.0619 | 6.0163 | 740 | 0.3797 | | 0.0393 | 6.0976 | 750 | 0.3781 | | 0.0391 | 6.1789 | 760 | 0.3767 | | 0.0383 | 6.2602 | 770 | 0.3746 | | 0.041 | 6.3415 | 780 | 0.3731 | | 0.0359 | 6.4228 | 790 | 0.3716 | | 0.0448 | 6.5041 | 800 | 0.3709 | | 0.0379 | 6.5854 | 810 | 0.3697 | | 0.0434 | 6.6667 | 820 | 0.3693 | | 0.0503 | 6.7480 | 830 | 0.3688 | | 0.04 | 6.8293 | 840 | 0.3684 | | 0.0378 | 6.9106 | 850 | 0.3682 | | 0.0441 | 6.9919 | 860 | 0.3675 | | 0.0344 | 7.0732 | 870 | 0.3669 | | 0.0401 | 7.1545 | 880 | 0.3662 | | 0.0516 | 7.2358 | 890 | 0.3654 | | 0.0309 | 7.3171 | 900 | 0.3654 | | 0.0314 | 7.3984 | 910 | 0.3653 | | 0.0403 | 7.4797 | 920 | 0.3650 | | 0.0459 | 7.5610 | 930 | 0.3646 | | 0.0299 | 7.6423 | 940 | 0.3642 | | 0.0337 | 7.7236 | 950 | 0.3638 | | 0.0352 | 7.8049 | 960 | 0.3636 | | 0.0598 | 7.8862 | 970 | 0.3635 | | 0.0421 | 7.9675 | 980 | 0.3630 | | 0.0409 | 8.0488 | 990 | 0.3628 | | 0.0369 | 8.1301 | 1000 | 0.3628 | ### Framework versions - PEFT 0.14.0 - Transformers 4.47.1 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0