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arabert_cross_relevance_task4_fold6

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  1. README.md +95 -90
README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: arabert_cross_relevance_task4_fold5
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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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  should probably proofread and complete it, then remove this comment. -->
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- # arabert_cross_relevance_task4_fold5
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1959
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- - Qwk: 0.3973
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- - Mse: 0.1959
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  ## Model description
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@@ -47,91 +47,96 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.1176 | 2 | 0.2829 | 0.2281 | 0.2825 |
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- | No log | 0.2353 | 4 | 0.3384 | 0.3607 | 0.3377 |
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- | No log | 0.3529 | 6 | 0.2361 | 0.3469 | 0.2356 |
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- | No log | 0.4706 | 8 | 0.2565 | 0.3434 | 0.2564 |
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- | No log | 0.5882 | 10 | 0.2109 | 0.3531 | 0.2109 |
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- | No log | 0.7059 | 12 | 0.1920 | 0.3266 | 0.1917 |
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- | No log | 0.8235 | 14 | 0.1946 | 0.3334 | 0.1943 |
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- | No log | 0.9412 | 16 | 0.1757 | 0.4574 | 0.1756 |
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- | No log | 1.0588 | 18 | 0.1726 | 0.5071 | 0.1727 |
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- | No log | 1.1765 | 20 | 0.1653 | 0.4079 | 0.1653 |
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- | No log | 1.2941 | 22 | 0.1708 | 0.3931 | 0.1707 |
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- | No log | 1.4118 | 24 | 0.1783 | 0.3512 | 0.1781 |
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- | No log | 1.5294 | 26 | 0.1810 | 0.3512 | 0.1809 |
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- | No log | 1.6471 | 28 | 0.1836 | 0.3467 | 0.1835 |
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- | No log | 1.7647 | 30 | 0.1863 | 0.3686 | 0.1862 |
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- | No log | 1.8824 | 32 | 0.1946 | 0.3724 | 0.1944 |
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- | No log | 2.0 | 34 | 0.1957 | 0.3890 | 0.1956 |
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- | No log | 2.1176 | 36 | 0.1833 | 0.3976 | 0.1833 |
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- | No log | 2.2353 | 38 | 0.1883 | 0.3683 | 0.1884 |
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- | No log | 2.3529 | 40 | 0.1889 | 0.3608 | 0.1889 |
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- | No log | 2.4706 | 42 | 0.1805 | 0.3872 | 0.1805 |
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- | No log | 2.5882 | 44 | 0.1951 | 0.4399 | 0.1949 |
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- | No log | 2.7059 | 46 | 0.2076 | 0.4132 | 0.2074 |
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- | No log | 2.8235 | 48 | 0.1906 | 0.4472 | 0.1904 |
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- | No log | 2.9412 | 50 | 0.1805 | 0.4286 | 0.1806 |
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- | No log | 3.0588 | 52 | 0.1962 | 0.3808 | 0.1964 |
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- | No log | 3.1765 | 54 | 0.1906 | 0.3696 | 0.1907 |
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- | No log | 3.2941 | 56 | 0.1903 | 0.3562 | 0.1903 |
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- | No log | 3.4118 | 58 | 0.1893 | 0.3519 | 0.1893 |
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- | No log | 3.5294 | 60 | 0.1793 | 0.3754 | 0.1793 |
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- | No log | 3.6471 | 62 | 0.1725 | 0.3761 | 0.1726 |
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- | No log | 3.7647 | 64 | 0.1732 | 0.3867 | 0.1732 |
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- | No log | 3.8824 | 66 | 0.1756 | 0.3728 | 0.1757 |
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- | No log | 4.0 | 68 | 0.1756 | 0.3768 | 0.1756 |
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- | No log | 4.1176 | 70 | 0.1760 | 0.3788 | 0.1760 |
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- | No log | 4.2353 | 72 | 0.1762 | 0.3724 | 0.1762 |
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- | No log | 4.3529 | 74 | 0.1718 | 0.3623 | 0.1717 |
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- | No log | 4.4706 | 76 | 0.1679 | 0.3667 | 0.1679 |
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- | No log | 4.5882 | 78 | 0.1666 | 0.3816 | 0.1667 |
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- | No log | 4.7059 | 80 | 0.1776 | 0.3966 | 0.1778 |
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- | No log | 4.8235 | 82 | 0.1888 | 0.3969 | 0.1890 |
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- | No log | 4.9412 | 84 | 0.1893 | 0.3969 | 0.1895 |
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- | No log | 5.0588 | 86 | 0.1782 | 0.3768 | 0.1783 |
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- | No log | 5.1765 | 88 | 0.1774 | 0.3683 | 0.1774 |
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- | No log | 5.2941 | 90 | 0.1798 | 0.3744 | 0.1797 |
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- | No log | 5.4118 | 92 | 0.1823 | 0.3684 | 0.1822 |
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- | No log | 5.5294 | 94 | 0.1828 | 0.3752 | 0.1827 |
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- | No log | 5.6471 | 96 | 0.1843 | 0.3774 | 0.1843 |
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- | No log | 5.7647 | 98 | 0.1901 | 0.3698 | 0.1901 |
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- | No log | 5.8824 | 100 | 0.1920 | 0.3735 | 0.1921 |
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- | No log | 6.0 | 102 | 0.1844 | 0.3821 | 0.1845 |
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- | No log | 6.1176 | 104 | 0.1765 | 0.4146 | 0.1766 |
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- | No log | 6.2353 | 106 | 0.1765 | 0.4100 | 0.1765 |
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- | No log | 6.3529 | 108 | 0.1783 | 0.4054 | 0.1783 |
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- | No log | 6.4706 | 110 | 0.1769 | 0.3909 | 0.1769 |
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- | No log | 6.5882 | 112 | 0.1761 | 0.3945 | 0.1762 |
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- | No log | 6.7059 | 114 | 0.1788 | 0.3862 | 0.1789 |
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- | No log | 6.8235 | 116 | 0.1789 | 0.3906 | 0.1789 |
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- | No log | 6.9412 | 118 | 0.1803 | 0.4054 | 0.1804 |
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- | No log | 7.0588 | 120 | 0.1833 | 0.3980 | 0.1834 |
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- | No log | 7.1765 | 122 | 0.1902 | 0.4017 | 0.1903 |
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- | No log | 7.2941 | 124 | 0.1979 | 0.4022 | 0.1981 |
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- | No log | 7.4118 | 126 | 0.1996 | 0.3880 | 0.1998 |
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- | No log | 7.5294 | 128 | 0.1940 | 0.3978 | 0.1941 |
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- | No log | 7.6471 | 130 | 0.1917 | 0.4072 | 0.1918 |
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- | No log | 7.7647 | 132 | 0.1940 | 0.3980 | 0.1940 |
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- | No log | 7.8824 | 134 | 0.2019 | 0.3978 | 0.2020 |
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- | No log | 8.0 | 136 | 0.2093 | 0.4067 | 0.2094 |
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- | No log | 8.1176 | 138 | 0.2156 | 0.3976 | 0.2157 |
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- | No log | 8.2353 | 140 | 0.2077 | 0.4067 | 0.2078 |
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- | No log | 8.3529 | 142 | 0.1994 | 0.4031 | 0.1995 |
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- | No log | 8.4706 | 144 | 0.1959 | 0.4118 | 0.1960 |
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- | No log | 8.5882 | 146 | 0.1952 | 0.4068 | 0.1953 |
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- | No log | 8.7059 | 148 | 0.1954 | 0.4021 | 0.1955 |
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- | No log | 8.8235 | 150 | 0.1949 | 0.3954 | 0.1950 |
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- | No log | 8.9412 | 152 | 0.1945 | 0.3906 | 0.1945 |
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- | No log | 9.0588 | 154 | 0.1941 | 0.3852 | 0.1941 |
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- | No log | 9.1765 | 156 | 0.1942 | 0.3755 | 0.1942 |
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- | No log | 9.2941 | 158 | 0.1931 | 0.3852 | 0.1931 |
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- | No log | 9.4118 | 160 | 0.1927 | 0.3852 | 0.1927 |
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- | No log | 9.5294 | 162 | 0.1933 | 0.3941 | 0.1933 |
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- | No log | 9.6471 | 164 | 0.1939 | 0.3941 | 0.1940 |
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- | No log | 9.7647 | 166 | 0.1946 | 0.3957 | 0.1947 |
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- | No log | 9.8824 | 168 | 0.1954 | 0.3973 | 0.1955 |
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- | No log | 10.0 | 170 | 0.1959 | 0.3973 | 0.1959 |
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task4_fold6
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # arabert_cross_relevance_task4_fold6
14
 
15
  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
16
  It achieves the following results on the evaluation set:
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+ - Loss: 0.3394
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+ - Qwk: 0.1601
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+ - Mse: 0.3398
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.1111 | 2 | 0.4458 | 0.0318 | 0.4461 |
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+ | No log | 0.2222 | 4 | 0.3469 | 0.0319 | 0.3472 |
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+ | No log | 0.3333 | 6 | 0.3536 | 0.0805 | 0.3537 |
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+ | No log | 0.4444 | 8 | 0.3107 | 0.0717 | 0.3106 |
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+ | No log | 0.5556 | 10 | 0.2972 | 0.1151 | 0.2971 |
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+ | No log | 0.6667 | 12 | 0.2762 | 0.1226 | 0.2762 |
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+ | No log | 0.7778 | 14 | 0.2644 | 0.1492 | 0.2647 |
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+ | No log | 0.8889 | 16 | 0.2552 | 0.1559 | 0.2557 |
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+ | No log | 1.0 | 18 | 0.2658 | 0.2351 | 0.2661 |
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+ | No log | 1.1111 | 20 | 0.2702 | 0.2761 | 0.2706 |
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+ | No log | 1.2222 | 22 | 0.2662 | 0.2796 | 0.2669 |
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+ | No log | 1.3333 | 24 | 0.2499 | 0.2669 | 0.2508 |
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+ | No log | 1.4444 | 26 | 0.2460 | 0.2651 | 0.2468 |
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+ | No log | 1.5556 | 28 | 0.2523 | 0.2545 | 0.2531 |
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+ | No log | 1.6667 | 30 | 0.2554 | 0.2137 | 0.2561 |
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+ | No log | 1.7778 | 32 | 0.2471 | 0.2220 | 0.2478 |
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+ | No log | 1.8889 | 34 | 0.2416 | 0.2899 | 0.2423 |
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+ | No log | 2.0 | 36 | 0.2485 | 0.2753 | 0.2491 |
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+ | No log | 2.1111 | 38 | 0.2427 | 0.2134 | 0.2433 |
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+ | No log | 2.2222 | 40 | 0.2377 | 0.2055 | 0.2383 |
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+ | No log | 2.3333 | 42 | 0.2333 | 0.2092 | 0.2338 |
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+ | No log | 2.4444 | 44 | 0.2390 | 0.2332 | 0.2394 |
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+ | No log | 2.5556 | 46 | 0.2482 | 0.2477 | 0.2487 |
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+ | No log | 2.6667 | 48 | 0.2585 | 0.2256 | 0.2591 |
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+ | No log | 2.7778 | 50 | 0.2626 | 0.2812 | 0.2633 |
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+ | No log | 2.8889 | 52 | 0.2502 | 0.2684 | 0.2508 |
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+ | No log | 3.0 | 54 | 0.2402 | 0.1962 | 0.2407 |
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+ | No log | 3.1111 | 56 | 0.2434 | 0.1883 | 0.2439 |
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+ | No log | 3.2222 | 58 | 0.2516 | 0.2024 | 0.2522 |
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+ | No log | 3.3333 | 60 | 0.2671 | 0.3187 | 0.2678 |
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+ | No log | 3.4444 | 62 | 0.2665 | 0.2324 | 0.2672 |
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+ | No log | 3.5556 | 64 | 0.2719 | 0.1977 | 0.2725 |
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+ | No log | 3.6667 | 66 | 0.2689 | 0.2130 | 0.2695 |
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+ | No log | 3.7778 | 68 | 0.2612 | 0.2140 | 0.2618 |
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+ | No log | 3.8889 | 70 | 0.2566 | 0.2395 | 0.2572 |
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+ | No log | 4.0 | 72 | 0.2553 | 0.2583 | 0.2560 |
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+ | No log | 4.1111 | 74 | 0.2604 | 0.2476 | 0.2610 |
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+ | No log | 4.2222 | 76 | 0.2643 | 0.2402 | 0.2649 |
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+ | No log | 4.3333 | 78 | 0.2719 | 0.2220 | 0.2725 |
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+ | No log | 4.4444 | 80 | 0.2816 | 0.1895 | 0.2822 |
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+ | No log | 4.5556 | 82 | 0.2776 | 0.2106 | 0.2783 |
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+ | No log | 4.6667 | 84 | 0.2758 | 0.2275 | 0.2765 |
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+ | No log | 4.7778 | 86 | 0.2876 | 0.2033 | 0.2882 |
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+ | No log | 4.8889 | 88 | 0.3127 | 0.1941 | 0.3132 |
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+ | No log | 5.0 | 90 | 0.3256 | 0.1643 | 0.3260 |
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+ | No log | 5.1111 | 92 | 0.3061 | 0.1895 | 0.3065 |
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+ | No log | 5.2222 | 94 | 0.2811 | 0.2186 | 0.2816 |
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+ | No log | 5.3333 | 96 | 0.2823 | 0.2186 | 0.2827 |
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+ | No log | 5.4444 | 98 | 0.2910 | 0.2137 | 0.2913 |
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+ | No log | 5.5556 | 100 | 0.3094 | 0.2076 | 0.3096 |
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+ | No log | 5.6667 | 102 | 0.3152 | 0.2118 | 0.3154 |
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+ | No log | 5.7778 | 104 | 0.3477 | 0.1897 | 0.3478 |
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+ | No log | 5.8889 | 106 | 0.3597 | 0.1780 | 0.3598 |
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+ | No log | 6.0 | 108 | 0.3476 | 0.1780 | 0.3479 |
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+ | No log | 6.1111 | 110 | 0.3267 | 0.1992 | 0.3272 |
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+ | No log | 6.2222 | 112 | 0.3089 | 0.2125 | 0.3095 |
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+ | No log | 6.3333 | 114 | 0.3128 | 0.1908 | 0.3134 |
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+ | No log | 6.4444 | 116 | 0.3211 | 0.1742 | 0.3215 |
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+ | No log | 6.5556 | 118 | 0.3339 | 0.1590 | 0.3343 |
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+ | No log | 6.6667 | 120 | 0.3109 | 0.1741 | 0.3113 |
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+ | No log | 6.7778 | 122 | 0.2827 | 0.2060 | 0.2832 |
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+ | No log | 6.8889 | 124 | 0.2767 | 0.2060 | 0.2772 |
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+ | No log | 7.0 | 126 | 0.2730 | 0.2130 | 0.2736 |
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+ | No log | 7.1111 | 128 | 0.2806 | 0.2009 | 0.2812 |
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+ | No log | 7.2222 | 130 | 0.2954 | 0.2098 | 0.2959 |
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+ | No log | 7.3333 | 132 | 0.3020 | 0.2033 | 0.3025 |
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+ | No log | 7.4444 | 134 | 0.3007 | 0.2098 | 0.3012 |
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+ | No log | 7.5556 | 136 | 0.2958 | 0.2054 | 0.2964 |
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+ | No log | 7.6667 | 138 | 0.3086 | 0.1781 | 0.3091 |
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+ | No log | 7.7778 | 140 | 0.3217 | 0.1623 | 0.3222 |
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+ | No log | 7.8889 | 142 | 0.3310 | 0.1677 | 0.3315 |
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+ | No log | 8.0 | 144 | 0.3269 | 0.1668 | 0.3274 |
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+ | No log | 8.1111 | 146 | 0.3173 | 0.1682 | 0.3179 |
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+ | No log | 8.2222 | 148 | 0.3173 | 0.1682 | 0.3178 |
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+ | No log | 8.3333 | 150 | 0.3261 | 0.1634 | 0.3266 |
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+ | No log | 8.4444 | 152 | 0.3255 | 0.1634 | 0.3259 |
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+ | No log | 8.5556 | 154 | 0.3229 | 0.1711 | 0.3234 |
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+ | No log | 8.6667 | 156 | 0.3219 | 0.1668 | 0.3225 |
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+ | No log | 8.7778 | 158 | 0.3264 | 0.1634 | 0.3269 |
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+ | No log | 8.8889 | 160 | 0.3314 | 0.1558 | 0.3319 |
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+ | No log | 9.0 | 162 | 0.3302 | 0.1558 | 0.3307 |
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+ | No log | 9.1111 | 164 | 0.3292 | 0.1601 | 0.3297 |
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+ | No log | 9.2222 | 166 | 0.3320 | 0.1601 | 0.3325 |
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+ | No log | 9.3333 | 168 | 0.3371 | 0.1601 | 0.3376 |
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+ | No log | 9.4444 | 170 | 0.3396 | 0.1601 | 0.3400 |
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+ | No log | 9.5556 | 172 | 0.3414 | 0.1601 | 0.3418 |
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+ | No log | 9.6667 | 174 | 0.3407 | 0.1601 | 0.3411 |
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+ | No log | 9.7778 | 176 | 0.3400 | 0.1601 | 0.3404 |
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+ | No log | 9.8889 | 178 | 0.3392 | 0.1601 | 0.3396 |
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+ | No log | 10.0 | 180 | 0.3394 | 0.1601 | 0.3398 |
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  ### Framework versions