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nomnoos37/stt-turbo-1226-v1.4

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README.md ADDED
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+ ---
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+ library_name: peft
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+ language:
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+ - ko
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+ license: mit
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+ base_model: openai/whisper-large-v3-turbo
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: Whisper Small ko
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Whisper Small ko
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0820
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 64
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+ - eval_batch_size: 256
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 200
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+ - training_steps: 2000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:----:|:---------------:|
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+ | 0.9031 | 0.0813 | 10 | 1.5890 |
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+ | 0.919 | 0.1626 | 20 | 1.5737 |
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+ | 0.8656 | 0.2439 | 30 | 1.5449 |
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+ | 0.8302 | 0.3252 | 40 | 1.4914 |
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+ | 0.7353 | 0.4065 | 50 | 1.3898 |
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+ | 0.5881 | 0.4878 | 60 | 1.1693 |
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+ | 0.35 | 0.5691 | 70 | 0.9472 |
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+ | 0.2397 | 0.6504 | 80 | 0.8734 |
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+ | 0.2272 | 0.7317 | 90 | 0.8072 |
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+ | 0.1772 | 0.8130 | 100 | 0.7618 |
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+ | 0.1426 | 0.8943 | 110 | 0.7191 |
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+ | 0.1226 | 0.9756 | 120 | 0.6701 |
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+ | 0.1022 | 1.0569 | 130 | 0.6356 |
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+ | 0.0866 | 1.1382 | 140 | 0.6036 |
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+ | 0.0796 | 1.2195 | 150 | 0.5758 |
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+ | 0.0886 | 1.3008 | 160 | 0.5459 |
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+ | 0.0648 | 1.3821 | 170 | 0.5246 |
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+ | 0.0716 | 1.4634 | 180 | 0.5128 |
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+ | 0.0571 | 1.5447 | 190 | 0.5002 |
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+ | 0.0861 | 1.6260 | 200 | 0.4762 |
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+ | 0.0594 | 1.7073 | 210 | 0.4489 |
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+ | 0.0494 | 1.7886 | 220 | 0.4278 |
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+ | 0.0414 | 1.8699 | 230 | 0.4159 |
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+ | 0.0457 | 1.9512 | 240 | 0.4106 |
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+ | 0.0408 | 2.0325 | 250 | 0.4002 |
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+ | 0.0469 | 2.1138 | 260 | 0.3972 |
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+ | 0.0588 | 2.1951 | 270 | 0.3853 |
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+ | 0.0397 | 2.2764 | 280 | 0.3816 |
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+ | 0.0459 | 2.3577 | 290 | 0.3806 |
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+ | 0.0394 | 2.4390 | 300 | 0.3644 |
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+ | 0.0376 | 2.5203 | 310 | 0.3562 |
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+ | 0.0376 | 2.6016 | 320 | 0.3461 |
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+ | 0.0321 | 2.6829 | 330 | 0.3337 |
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+ | 0.037 | 2.7642 | 340 | 0.3301 |
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+ | 0.0377 | 2.8455 | 350 | 0.3240 |
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+ | 0.0245 | 2.9268 | 360 | 0.3185 |
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+ | 0.0361 | 3.0081 | 370 | 0.3179 |
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+ | 0.0279 | 3.0894 | 380 | 0.3130 |
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+ | 0.0338 | 3.1707 | 390 | 0.3066 |
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+ | 0.0344 | 3.2520 | 400 | 0.3010 |
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+ | 0.0279 | 3.3333 | 410 | 0.2959 |
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+ | 0.0243 | 3.4146 | 420 | 0.2886 |
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+ | 0.0346 | 3.4959 | 430 | 0.2899 |
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+ | 0.0251 | 3.5772 | 440 | 0.2851 |
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+ | 0.0475 | 3.6585 | 450 | 0.2755 |
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+ | 0.0272 | 3.7398 | 460 | 0.2714 |
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+ | 0.0242 | 3.8211 | 470 | 0.2719 |
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+ | 0.0238 | 3.9024 | 480 | 0.2707 |
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+ | 0.0235 | 3.9837 | 490 | 0.2688 |
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+ | 0.0293 | 4.0650 | 500 | 0.2677 |
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+ | 0.0211 | 4.1463 | 510 | 0.2641 |
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+ | 0.0205 | 4.2276 | 520 | 0.2601 |
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+ | 0.0228 | 4.3089 | 530 | 0.2553 |
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+ | 0.0216 | 4.3902 | 540 | 0.2538 |
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+ | 0.0247 | 4.4715 | 550 | 0.2522 |
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+ | 0.0413 | 4.5528 | 560 | 0.2484 |
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+ | 0.0195 | 4.6341 | 570 | 0.2399 |
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+ | 0.0211 | 4.7154 | 580 | 0.2392 |
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+ | 0.0176 | 4.7967 | 590 | 0.2457 |
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+ | 0.0251 | 4.8780 | 600 | 0.2409 |
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+ | 0.0213 | 4.9593 | 610 | 0.2332 |
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+ | 0.0236 | 5.0407 | 620 | 0.2354 |
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+ | 0.0181 | 5.1220 | 630 | 0.2347 |
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+ | 0.0194 | 5.2033 | 640 | 0.2353 |
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+ | 0.0174 | 5.2846 | 650 | 0.2340 |
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+ | 0.0169 | 5.3659 | 660 | 0.2296 |
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+ | 0.0193 | 5.4472 | 670 | 0.2252 |
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+ | 0.0161 | 5.5285 | 680 | 0.2230 |
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+ | 0.02 | 5.6098 | 690 | 0.2254 |
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+ | 0.0185 | 5.6911 | 700 | 0.2251 |
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+ | 0.0185 | 5.7724 | 710 | 0.2211 |
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+ | 0.0141 | 5.8537 | 720 | 0.2191 |
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+ | 0.0198 | 5.9350 | 730 | 0.2226 |
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+ | 0.0427 | 6.0163 | 740 | 0.2130 |
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+ | 0.0147 | 6.0976 | 750 | 0.2478 |
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+ | 0.0139 | 6.1789 | 760 | 0.2450 |
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+ | 0.0149 | 6.2602 | 770 | 0.2423 |
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+ | 0.0161 | 6.3415 | 780 | 0.2384 |
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+ | 0.0148 | 6.4228 | 790 | 0.2347 |
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+ | 0.043 | 6.7480 | 830 | 0.1678 |
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+ | 0.0147 | 6.8293 | 840 | 0.1679 |
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+ | 0.0167 | 6.9106 | 850 | 0.1645 |
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+ | 0.017 | 6.9919 | 860 | 0.1646 |
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+ | 0.0118 | 7.0732 | 870 | 0.1650 |
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+ | 0.0125 | 7.1545 | 880 | 0.1635 |
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+ | 0.0194 | 7.2358 | 890 | 0.1617 |
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+ | 0.0094 | 7.6423 | 940 | 0.1554 |
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+ | 0.0116 | 7.8049 | 960 | 0.1531 |
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+ | 0.0295 | 7.8862 | 970 | 0.1472 |
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+ | 0.0155 | 7.9675 | 980 | 0.1497 |
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+ | 0.0144 | 8.0488 | 990 | 0.1507 |
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+ | 0.0109 | 8.1301 | 1000 | 0.1503 |
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+ | 0.0257 | 8.2114 | 1010 | 0.1361 |
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+ | 0.0092 | 8.2927 | 1020 | 0.1399 |
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+ | 0.0146 | 8.7805 | 1080 | 0.1399 |
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+ | 0.0109 | 8.8618 | 1090 | 0.1370 |
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+ | 0.0083 | 9.0244 | 1110 | 0.1363 |
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+ | 0.0113 | 9.1057 | 1120 | 0.1379 |
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+ | 0.0212 | 9.1870 | 1130 | 0.1272 |
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+ | 0.0086 | 9.2683 | 1140 | 0.1267 |
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+ | 0.0131 | 9.3496 | 1150 | 0.1281 |
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+ | 0.0093 | 9.4309 | 1160 | 0.1274 |
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+ | 0.0115 | 9.5935 | 1180 | 0.1253 |
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+ | 0.0093 | 9.6748 | 1190 | 0.1227 |
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+ | 0.0101 | 9.8374 | 1210 | 0.1218 |
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+ | 0.0129 | 9.9187 | 1220 | 0.1227 |
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+ | 0.0084 | 10.0 | 1230 | 0.1225 |
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+ | 0.0081 | 13.0894 | 1610 | 0.0905 |
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+ | 0.0053 | 14.8780 | 1830 | 0.0840 |
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+ | 0.0063 | 15.0407 | 1850 | 0.0834 |
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+ | 0.006 | 15.1220 | 1860 | 0.0832 |
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+ | 0.0056 | 15.2846 | 1880 | 0.0830 |
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+ | 0.0056 | 15.3659 | 1890 | 0.0827 |
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+ | 0.0069 | 15.4472 | 1900 | 0.0825 |
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+ | 0.0061 | 15.5285 | 1910 | 0.0825 |
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+ | 0.0067 | 16.0163 | 1970 | 0.0821 |
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+ | 0.0053 | 16.2602 | 2000 | 0.0820 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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