--- library_name: transformers language: - ko license: apache-2.0 base_model: openai/whisper-base tags: - hf-asr-leaderboard - generated_from_trainer datasets: - hyk000/gdialect model-index: - name: gg_mdl results: [] --- # gg_mdl This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the gg_ds dataset. It achieves the following results on the evaluation set: - Loss: 1.7053 - Cer: 26.9304 ## 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: 4 - eval_batch_size: 4 - 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: 100000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | |:-------------:|:-----:|:------:|:---------------:|:-------:| | 0.2863 | 0.8 | 1000 | 0.9834 | 34.5643 | | 0.3725 | 1.6 | 2000 | 0.9299 | 36.7432 | | 0.3335 | 2.4 | 3000 | 0.9437 | 32.7097 | | 0.1498 | 3.2 | 4000 | 0.9722 | 26.1319 | | 0.2081 | 4.0 | 5000 | 0.9881 | 31.9533 | | 0.213 | 4.8 | 6000 | 1.0197 | 30.8832 | | 0.094 | 5.6 | 7000 | 1.0486 | 29.5707 | | 0.0637 | 6.4 | 8000 | 1.0741 | 26.9211 | | 0.0518 | 7.2 | 9000 | 1.0964 | 30.4382 | | 0.0512 | 8.0 | 10000 | 1.1179 | 26.4199 | | 0.0288 | 8.8 | 11000 | 1.1420 | 27.2981 | | 0.0274 | 9.6 | 12000 | 1.1617 | 26.9620 | | 0.0255 | 10.4 | 13000 | 1.1779 | 27.3133 | | 0.0215 | 11.2 | 14000 | 1.2062 | 25.8813 | | 0.0128 | 12.0 | 15000 | 1.2138 | 25.8497 | | 0.013 | 12.8 | 16000 | 1.2354 | 26.8496 | | 0.0054 | 13.6 | 17000 | 1.2323 | 27.6025 | | 0.0088 | 14.4 | 18000 | 1.2596 | 25.8228 | | 0.0031 | 15.2 | 19000 | 1.2807 | 29.0122 | | 0.0093 | 16.0 | 20000 | 1.2865 | 25.8907 | | 0.0113 | 16.8 | 21000 | 1.2983 | 28.7241 | | 0.0051 | 17.6 | 22000 | 1.3118 | 25.8685 | | 0.0019 | 18.4 | 23000 | 1.3225 | 26.2256 | | 0.0031 | 19.2 | 24000 | 1.3419 | 25.9586 | | 0.0096 | 20.0 | 25000 | 1.3516 | 28.7066 | | 0.0051 | 20.8 | 26000 | 1.3419 | 25.9937 | | 0.0028 | 21.6 | 27000 | 1.3634 | 28.4256 | | 0.0019 | 22.4 | 28000 | 1.3659 | 26.7876 | | 0.0041 | 23.2 | 29000 | 1.3855 | 25.7631 | | 0.005 | 24.0 | 30000 | 1.3848 | 27.5709 | | 0.0043 | 24.8 | 31000 | 1.3801 | 27.5252 | | 0.0046 | 25.6 | 32000 | 1.3974 | 26.5253 | | 0.0017 | 26.4 | 33000 | 1.3992 | 26.9854 | | 0.0017 | 27.2 | 34000 | 1.4133 | 26.5405 | | 0.0007 | 28.0 | 35000 | 1.4214 | 27.7360 | | 0.0009 | 28.8 | 36000 | 1.4275 | 28.0322 | | 0.0018 | 29.6 | 37000 | 1.4315 | 26.6939 | | 0.0012 | 30.4 | 38000 | 1.4424 | 26.2431 | | 0.0007 | 31.2 | 39000 | 1.4498 | 26.0640 | | 0.0007 | 32.0 | 40000 | 1.4652 | 27.6891 | | 0.001 | 32.8 | 41000 | 1.4652 | 26.2478 | | 0.0003 | 33.6 | 42000 | 1.4696 | 26.8297 | | 0.0004 | 34.4 | 43000 | 1.4603 | 26.3309 | | 0.0004 | 35.2 | 44000 | 1.4692 | 26.9234 | | 0.0003 | 36.0 | 45000 | 1.4689 | 26.7981 | | 0.001 | 36.8 | 46000 | 1.4907 | 26.5323 | | 0.0015 | 37.6 | 47000 | 1.4897 | 26.7817 | | 0.0002 | 38.4 | 48000 | 1.4874 | 26.9093 | | 0.0003 | 39.2 | 49000 | 1.4884 | 26.8637 | | 0.0009 | 40.0 | 50000 | 1.4854 | 26.9386 | | 0.001 | 40.8 | 51000 | 1.4978 | 26.8449 | | 0.0002 | 41.6 | 52000 | 1.5018 | 27.8132 | | 0.0007 | 42.4 | 53000 | 1.5129 | 27.7219 | | 0.0002 | 43.2 | 54000 | 1.5252 | 27.9010 | | 0.0024 | 44.0 | 55000 | 1.5070 | 25.5617 | | 0.0007 | 44.8 | 56000 | 1.5149 | 27.3964 | | 0.0025 | 45.6 | 57000 | 1.5287 | 25.9973 | | 0.0004 | 46.4 | 58000 | 1.5313 | 27.6294 | | 0.0001 | 47.2 | 59000 | 1.5313 | 26.6799 | | 0.0005 | 48.0 | 60000 | 1.5478 | 27.5381 | | 0.0003 | 48.8 | 61000 | 1.5353 | 27.3402 | | 0.0001 | 49.6 | 62000 | 1.5550 | 25.4680 | | 0.0001 | 50.4 | 63000 | 1.5463 | 25.9656 | | 0.0001 | 51.2 | 64000 | 1.5609 | 26.2935 | | 0.0001 | 52.0 | 65000 | 1.5556 | 25.8509 | | 0.0012 | 52.8 | 66000 | 1.5704 | 26.3110 | | 0.0007 | 53.6 | 67000 | 1.5673 | 26.3087 | | 0.0003 | 54.4 | 68000 | 1.5767 | 26.2396 | | 0.0 | 55.2 | 69000 | 1.5727 | 26.2139 | | 0.0001 | 56.0 | 70000 | 1.5723 | 27.4116 | | 0.0001 | 56.8 | 71000 | 1.5863 | 26.9082 | | 0.0004 | 57.6 | 72000 | 1.5943 | 26.4949 | | 0.0006 | 58.4 | 73000 | 1.5944 | 26.6330 | | 0.0001 | 59.2 | 74000 | 1.5860 | 28.3659 | | 0.0 | 60.0 | 75000 | 1.5973 | 26.7759 | | 0.0 | 60.8 | 76000 | 1.6017 | 27.2278 | | 0.0 | 61.6 | 77000 | 1.6070 | 26.2619 | | 0.0 | 62.4 | 78000 | 1.6092 | 27.0030 | | 0.0 | 63.2 | 79000 | 1.6108 | 26.6576 | | 0.0 | 64.0 | 80000 | 1.6146 | 25.9387 | | 0.0 | 64.8 | 81000 | 1.6202 | 25.7291 | | 0.0 | 65.6 | 82000 | 1.6215 | 27.0042 | | 0.0 | 66.4 | 83000 | 1.6256 | 27.1915 | | 0.0 | 67.2 | 84000 | 1.6330 | 26.7677 | | 0.0 | 68.0 | 85000 | 1.6279 | 26.5803 | | 0.0 | 68.8 | 86000 | 1.6343 | 26.8625 | | 0.0 | 69.6 | 87000 | 1.6417 | 26.1296 | | 0.0 | 70.4 | 88000 | 1.6505 | 26.5874 | | 0.0 | 71.2 | 89000 | 1.6558 | 26.0640 | | 0.0 | 72.0 | 90000 | 1.6602 | 25.9469 | | 0.0 | 72.8 | 91000 | 1.6662 | 26.2338 | | 0.0 | 73.6 | 92000 | 1.6719 | 26.1460 | | 0.0 | 74.4 | 93000 | 1.6783 | 26.6576 | | 0.0 | 75.2 | 94000 | 1.6836 | 26.3099 | | 0.0 | 76.0 | 95000 | 1.6891 | 26.4984 | | 0.0 | 76.8 | 96000 | 1.6946 | 26.4328 | | 0.0 | 77.6 | 97000 | 1.6988 | 26.7056 | | 0.0 | 78.4 | 98000 | 1.7023 | 26.6049 | | 0.0 | 79.2 | 99000 | 1.7046 | 27.1821 | | 0.0 | 80.0 | 100000 | 1.7053 | 26.9304 | ### Framework versions - Transformers 4.47.0.dev0 - Pytorch 2.4.1 - Datasets 3.1.0 - Tokenizers 0.20.1