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update model card README.md
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README.md
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- stereoset
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metrics:
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- accuracy
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model-index:
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- name: xlnet-base-cased_stereoset_classifieronly
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: stereoset
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type: stereoset
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config: intersentence
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split: validation
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args: intersentence
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.5894819466248038
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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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# xlnet-base-cased_stereoset_classifieronly
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on
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It achieves the following results on the evaluation set:
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- Loss: 0.6646
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- Accuracy: 0.5895
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- Tp: 0.2998
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- Tn: 0.2896
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- Fp: 0.2229
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- Fn: 0.1876
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- lr_scheduler_type: linear
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- num_epochs: 50
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Tp | Tn | Fp | Fn |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
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| 0.7171 | 0.43 | 20 | 0.6989 | 0.5196 | 0.3556 | 0.1641 | 0.3485 | 0.1319 |
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| 0.7037 | 0.85 | 40 | 0.6923 | 0.5385 | 0.3438 | 0.1947 | 0.3179 | 0.1436 |
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| 0.7002 | 1.28 | 60 | 0.6834 | 0.5510 | 0.2551 | 0.2959 | 0.2166 | 0.2323 |
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| 0.6973 | 1.7 | 80 | 0.6839 | 0.5440 | 0.2983 | 0.2457 | 0.2669 | 0.1892 |
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| 0.7197 | 2.13 | 100 | 0.6852 | 0.5620 | 0.3713 | 0.1907 | 0.3218 | 0.1162 |
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| 0.7079 | 2.55 | 120 | 0.6776 | 0.5832 | 0.2520 | 0.3312 | 0.1813 | 0.2355 |
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| 0.6969 | 2.98 | 140 | 0.6918 | 0.5479 | 0.0903 | 0.4576 | 0.0549 | 0.3972 |
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| 0.6804 | 3.4 | 160 | 0.6776 | 0.5604 | 0.2865 | 0.2739 | 0.2386 | 0.2009 |
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| 0.7 | 3.83 | 180 | 0.6907 | 0.5510 | 0.4144 | 0.1366 | 0.3760 | 0.0730 |
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| 0.6778 | 4.26 | 200 | 0.6800 | 0.5714 | 0.1727 | 0.3987 | 0.1138 | 0.3148 |
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| 0.6719 | 4.68 | 220 | 0.6775 | 0.5801 | 0.2802 | 0.2998 | 0.2127 | 0.2072 |
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| 0.6996 | 5.11 | 240 | 0.6797 | 0.5675 | 0.2009 | 0.3666 | 0.1460 | 0.2865 |
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| 0.6903 | 5.53 | 260 | 0.6880 | 0.5581 | 0.1279 | 0.4301 | 0.0824 | 0.3595 |
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| 0.7007 | 5.96 | 280 | 0.6865 | 0.5644 | 0.1319 | 0.4325 | 0.0801 | 0.3556 |
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| 0.683 | 6.38 | 300 | 0.6801 | 0.5604 | 0.2174 | 0.3430 | 0.1695 | 0.2700 |
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| 0.6881 | 6.81 | 320 | 0.6802 | 0.5706 | 0.1962 | 0.3744 | 0.1381 | 0.2912 |
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| 0.692 | 7.23 | 340 | 0.6752 | 0.5589 | 0.2786 | 0.2802 | 0.2323 | 0.2088 |
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| 0.6714 | 7.66 | 360 | 0.6736 | 0.5785 | 0.2496 | 0.3289 | 0.1837 | 0.2378 |
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| 0.6746 | 8.09 | 380 | 0.6791 | 0.5769 | 0.1664 | 0.4105 | 0.1020 | 0.3210 |
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| 0.6899 | 8.51 | 400 | 0.6750 | 0.5840 | 0.2253 | 0.3587 | 0.1538 | 0.2622 |
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| 0.6861 | 8.94 | 420 | 0.6832 | 0.5636 | 0.3383 | 0.2253 | 0.2873 | 0.1491 |
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| 0.7008 | 9.36 | 440 | 0.6935 | 0.5589 | 0.1091 | 0.4498 | 0.0628 | 0.3783 |
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| 0.703 | 9.79 | 460 | 0.6736 | 0.5691 | 0.2598 | 0.3093 | 0.2033 | 0.2276 |
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| 0.675 | 10.21 | 480 | 0.6786 | 0.5612 | 0.3320 | 0.2292 | 0.2834 | 0.1554 |
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| 0.6795 | 10.64 | 500 | 0.6790 | 0.5675 | 0.2009 | 0.3666 | 0.1460 | 0.2865 |
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| 0.6892 | 11.06 | 520 | 0.6868 | 0.5581 | 0.3838 | 0.1743 | 0.3383 | 0.1036 |
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| 0.6768 | 11.49 | 540 | 0.6817 | 0.5581 | 0.3485 | 0.2096 | 0.3030 | 0.1389 |
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| 0.6833 | 11.91 | 560 | 0.6763 | 0.5620 | 0.2614 | 0.3006 | 0.2119 | 0.2261 |
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| 0.7076 | 12.34 | 580 | 0.6779 | 0.5856 | 0.2049 | 0.3807 | 0.1319 | 0.2826 |
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| 0.6893 | 12.77 | 600 | 0.6750 | 0.5785 | 0.2967 | 0.2818 | 0.2308 | 0.1907 |
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| 0.6826 | 13.19 | 620 | 0.6768 | 0.5659 | 0.3493 | 0.2166 | 0.2959 | 0.1381 |
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| 0.682 | 13.62 | 640 | 0.6756 | 0.5699 | 0.3367 | 0.2331 | 0.2794 | 0.1507 |
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| 0.692 | 14.04 | 660 | 0.6730 | 0.5738 | 0.3022 | 0.2716 | 0.2410 | 0.1852 |
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| 0.6976 | 14.47 | 680 | 0.6797 | 0.5801 | 0.1609 | 0.4192 | 0.0934 | 0.3265 |
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| 0.6758 | 14.89 | 700 | 0.6764 | 0.5738 | 0.1923 | 0.3815 | 0.1311 | 0.2951 |
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| 0.6826 | 15.32 | 720 | 0.6792 | 0.5832 | 0.3807 | 0.2025 | 0.3100 | 0.1068 |
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| 0.6826 | 15.74 | 740 | 0.6784 | 0.5691 | 0.3689 | 0.2002 | 0.3124 | 0.1185 |
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| 0.6577 | 16.17 | 760 | 0.6722 | 0.5911 | 0.3006 | 0.2904 | 0.2221 | 0.1868 |
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| 0.6838 | 16.6 | 780 | 0.6723 | 0.5754 | 0.2724 | 0.3030 | 0.2096 | 0.2151 |
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| 0.6754 | 17.02 | 800 | 0.6705 | 0.5769 | 0.2582 | 0.3187 | 0.1939 | 0.2292 |
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| 0.7018 | 17.45 | 820 | 0.6698 | 0.5738 | 0.2590 | 0.3148 | 0.1978 | 0.2284 |
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| 0.6864 | 17.87 | 840 | 0.6828 | 0.5620 | 0.3791 | 0.1829 | 0.3297 | 0.1083 |
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| 0.6714 | 18.3 | 860 | 0.6754 | 0.5722 | 0.3257 | 0.2465 | 0.2661 | 0.1617 |
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| 0.6773 | 18.72 | 880 | 0.6712 | 0.5840 | 0.2488 | 0.3352 | 0.1774 | 0.2386 |
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| 0.6696 | 19.15 | 900 | 0.6773 | 0.5761 | 0.3619 | 0.2143 | 0.2983 | 0.1256 |
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| 0.6778 | 19.57 | 920 | 0.6701 | 0.5793 | 0.2323 | 0.3469 | 0.1656 | 0.2551 |
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| 0.6814 | 20.0 | 940 | 0.6704 | 0.5801 | 0.2402 | 0.3399 | 0.1727 | 0.2473 |
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| 0.6834 | 20.43 | 960 | 0.6686 | 0.5785 | 0.2347 | 0.3438 | 0.1688 | 0.2527 |
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| 0.6824 | 20.85 | 980 | 0.6783 | 0.5651 | 0.3791 | 0.1860 | 0.3265 | 0.1083 |
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| 0.6693 | 21.28 | 1000 | 0.6726 | 0.5722 | 0.3399 | 0.2323 | 0.2802 | 0.1476 |
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| 0.6807 | 21.7 | 1020 | 0.6789 | 0.5683 | 0.3705 | 0.1978 | 0.3148 | 0.1170 |
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| 0.6598 | 22.13 | 1040 | 0.6719 | 0.5691 | 0.3085 | 0.2606 | 0.2520 | 0.1790 |
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| 0.6736 | 22.55 | 1060 | 0.6718 | 0.5793 | 0.3250 | 0.2543 | 0.2582 | 0.1625 |
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| 0.682 | 22.98 | 1080 | 0.6886 | 0.5542 | 0.4027 | 0.1515 | 0.3611 | 0.0848 |
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| 0.6726 | 23.4 | 1100 | 0.6759 | 0.5691 | 0.3469 | 0.2221 | 0.2904 | 0.1405 |
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| 0.6741 | 23.83 | 1120 | 0.6706 | 0.5793 | 0.3124 | 0.2669 | 0.2457 | 0.1750 |
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| 0.6737 | 24.26 | 1140 | 0.6705 | 0.5965 | 0.2661 | 0.3305 | 0.1821 | 0.2214 |
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| 0.6802 | 24.68 | 1160 | 0.6705 | 0.5848 | 0.2229 | 0.3619 | 0.1507 | 0.2645 |
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| 0.6801 | 25.11 | 1180 | 0.6784 | 0.5659 | 0.3776 | 0.1884 | 0.3242 | 0.1099 |
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| 0.6699 | 25.53 | 1200 | 0.6729 | 0.5746 | 0.3493 | 0.2253 | 0.2873 | 0.1381 |
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| 0.6793 | 25.96 | 1220 | 0.6696 | 0.5965 | 0.2504 | 0.3462 | 0.1664 | 0.2370 |
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| 0.6808 | 26.38 | 1240 | 0.6722 | 0.5730 | 0.3430 | 0.2300 | 0.2826 | 0.1444 |
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| 0.6802 | 26.81 | 1260 | 0.6681 | 0.5973 | 0.2896 | 0.3077 | 0.2049 | 0.1978 |
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| 0.6714 | 27.23 | 1280 | 0.6711 | 0.5785 | 0.3501 | 0.2284 | 0.2841 | 0.1374 |
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| 0.6559 | 27.66 | 1300 | 0.6712 | 0.5683 | 0.3438 | 0.2245 | 0.2881 | 0.1436 |
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| 0.6671 | 28.09 | 1320 | 0.6749 | 0.5691 | 0.3728 | 0.1962 | 0.3163 | 0.1146 |
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| 0.6935 | 28.51 | 1340 | 0.6679 | 0.5879 | 0.3218 | 0.2661 | 0.2465 | 0.1656 |
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| 0.6767 | 28.94 | 1360 | 0.6690 | 0.5856 | 0.3312 | 0.2543 | 0.2582 | 0.1562 |
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| 0.6773 | 29.36 | 1380 | 0.6741 | 0.5746 | 0.3666 | 0.2080 | 0.3046 | 0.1209 |
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| 0.6881 | 29.79 | 1400 | 0.6679 | 0.5934 | 0.2425 | 0.3509 | 0.1617 | 0.2449 |
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| 0.6773 | 30.21 | 1420 | 0.6672 | 0.5934 | 0.2849 | 0.3085 | 0.2041 | 0.2025 |
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| 0.6713 | 30.64 | 1440 | 0.6711 | 0.5808 | 0.3493 | 0.2316 | 0.2810 | 0.1381 |
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| 0.6797 | 31.06 | 1460 | 0.6666 | 0.5863 | 0.2810 | 0.3053 | 0.2072 | 0.2064 |
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| 0.6728 | 31.49 | 1480 | 0.6674 | 0.5863 | 0.3210 | 0.2653 | 0.2473 | 0.1664 |
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| 0.6752 | 31.91 | 1500 | 0.6660 | 0.5863 | 0.2959 | 0.2904 | 0.2221 | 0.1915 |
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| 0.6695 | 32.34 | 1520 | 0.6720 | 0.5848 | 0.3768 | 0.2080 | 0.3046 | 0.1107 |
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| 0.6857 | 32.77 | 1540 | 0.6658 | 0.5934 | 0.2480 | 0.3454 | 0.1672 | 0.2394 |
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| 0.6675 | 33.19 | 1560 | 0.6657 | 0.5950 | 0.3022 | 0.2928 | 0.2198 | 0.1852 |
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| 0.6719 | 33.62 | 1580 | 0.6671 | 0.5793 | 0.3289 | 0.2504 | 0.2622 | 0.1586 |
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| 0.684 | 34.04 | 1600 | 0.6659 | 0.5887 | 0.3053 | 0.2834 | 0.2292 | 0.1821 |
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| 0.6739 | 34.47 | 1620 | 0.6672 | 0.5832 | 0.3281 | 0.2551 | 0.2575 | 0.1593 |
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| 0.6774 | 34.89 | 1640 | 0.6655 | 0.5950 | 0.2991 | 0.2959 | 0.2166 | 0.1884 |
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| 0.6625 | 35.32 | 1660 | 0.6665 | 0.5785 | 0.3171 | 0.2614 | 0.2512 | 0.1703 |
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| 0.6739 | 35.74 | 1680 | 0.6653 | 0.5848 | 0.3077 | 0.2771 | 0.2355 | 0.1797 |
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| 0.6519 | 36.17 | 1700 | 0.6640 | 0.5895 | 0.2779 | 0.3116 | 0.2009 | 0.2096 |
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| 0.6646 | 36.6 | 1720 | 0.6744 | 0.5832 | 0.3925 | 0.1907 | 0.3218 | 0.0950 |
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| 0.6855 | 37.02 | 1740 | 0.6653 | 0.5950 | 0.3187 | 0.2763 | 0.2363 | 0.1688 |
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| 0.674 | 37.45 | 1760 | 0.6661 | 0.5895 | 0.3218 | 0.2677 | 0.2449 | 0.1656 |
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| 0.6688 | 37.87 | 1780 | 0.6664 | 0.5871 | 0.3140 | 0.2732 | 0.2394 | 0.1735 |
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| 0.659 | 38.3 | 1800 | 0.6661 | 0.5816 | 0.3038 | 0.2779 | 0.2347 | 0.1837 |
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| 0.6603 | 38.72 | 1820 | 0.6662 | 0.5856 | 0.3148 | 0.2708 | 0.2418 | 0.1727 |
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| 0.6622 | 39.15 | 1840 | 0.6660 | 0.5926 | 0.2245 | 0.3681 | 0.1444 | 0.2630 |
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| 0.6748 | 39.57 | 1860 | 0.6649 | 0.5903 | 0.2818 | 0.3085 | 0.2041 | 0.2057 |
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| 0.6749 | 40.0 | 1880 | 0.6653 | 0.5918 | 0.2943 | 0.2975 | 0.2151 | 0.1931 |
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| 0.6846 | 40.43 | 1900 | 0.6739 | 0.5691 | 0.3752 | 0.1939 | 0.3187 | 0.1122 |
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| 0.6695 | 40.85 | 1920 | 0.6644 | 0.5895 | 0.2488 | 0.3407 | 0.1719 | 0.2386 |
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| 0.6637 | 41.28 | 1940 | 0.6660 | 0.5903 | 0.3242 | 0.2661 | 0.2465 | 0.1633 |
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| 0.6796 | 41.7 | 1960 | 0.6665 | 0.5911 | 0.3281 | 0.2630 | 0.2496 | 0.1593 |
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| 0.671 | 42.13 | 1980 | 0.6640 | 0.5879 | 0.2826 | 0.3053 | 0.2072 | 0.2049 |
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| 0.683 | 42.55 | 2000 | 0.6639 | 0.5871 | 0.2794 | 0.3077 | 0.2049 | 0.2080 |
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| 0.6719 | 42.98 | 2020 | 0.6647 | 0.6028 | 0.3148 | 0.2881 | 0.2245 | 0.1727 |
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| 0.6604 | 43.4 | 2040 | 0.6639 | 0.5918 | 0.2598 | 0.3320 | 0.1805 | 0.2276 |
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| 0.6793 | 43.83 | 2060 | 0.6645 | 0.5918 | 0.2983 | 0.2936 | 0.2190 | 0.1892 |
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| 0.6727 | 44.26 | 2080 | 0.6669 | 0.5903 | 0.3359 | 0.2543 | 0.2582 | 0.1515 |
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| 0.6615 | 44.68 | 2100 | 0.6661 | 0.5926 | 0.3234 | 0.2692 | 0.2433 | 0.1641 |
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| 0.6624 | 45.11 | 2120 | 0.6651 | 0.5918 | 0.3093 | 0.2826 | 0.2300 | 0.1782 |
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| 0.6601 | 45.53 | 2140 | 0.6646 | 0.5918 | 0.2998 | 0.2920 | 0.2206 | 0.1876 |
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| 0.6924 | 45.96 | 2160 | 0.6643 | 0.5911 | 0.2849 | 0.3061 | 0.2064 | 0.2025 |
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| 0.6702 | 46.38 | 2180 | 0.6645 | 0.5895 | 0.2943 | 0.2951 | 0.2174 | 0.1931 |
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| 0.658 | 46.81 | 2200 | 0.6642 | 0.5918 | 0.2826 | 0.3093 | 0.2033 | 0.2049 |
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| 0.6613 | 47.23 | 2220 | 0.6642 | 0.5895 | 0.2849 | 0.3046 | 0.2080 | 0.2025 |
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| 0.6552 | 47.66 | 2240 | 0.6649 | 0.5911 | 0.3061 | 0.2849 | 0.2276 | 0.1813 |
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| 0.6605 | 48.09 | 2260 | 0.6649 | 0.5926 | 0.3069 | 0.2857 | 0.2268 | 0.1805 |
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| 0.6886 | 48.51 | 2280 | 0.6643 | 0.5887 | 0.2889 | 0.2998 | 0.2127 | 0.1986 |
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| 0.6692 | 48.94 | 2300 | 0.6645 | 0.5887 | 0.2951 | 0.2936 | 0.2190 | 0.1923 |
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| 0.6841 | 49.36 | 2320 | 0.6647 | 0.5918 | 0.3030 | 0.2889 | 0.2237 | 0.1845 |
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| 0.6724 | 49.79 | 2340 | 0.6646 | 0.5895 | 0.2998 | 0.2896 | 0.2229 | 0.1876 |
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### Framework versions
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- Transformers 4.26.1
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: xlnet-base-cased_stereoset_classifieronly
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results: []
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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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# xlnet-base-cased_stereoset_classifieronly
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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## Model description
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| 31 |
### Training hyperparameters
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| 32 |
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| 33 |
The following hyperparameters were used during training:
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+
- learning_rate: 5e-05
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| 35 |
- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- lr_scheduler_type: linear
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- num_epochs: 50
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| 41 |
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| 42 |
### Framework versions
|
| 43 |
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| 44 |
- Transformers 4.26.1
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