--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task3_fold5 results: [] --- # arabert_cross_relevance_task3_fold5 This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2278 - Qwk: 0.3503 - Mse: 0.2272 ## 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: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | No log | 0.125 | 2 | 0.4369 | 0.2251 | 0.4365 | | No log | 0.25 | 4 | 0.2909 | 0.1687 | 0.2903 | | No log | 0.375 | 6 | 0.2730 | 0.2811 | 0.2726 | | No log | 0.5 | 8 | 0.3037 | 0.3049 | 0.3032 | | No log | 0.625 | 10 | 0.2562 | 0.2310 | 0.2559 | | No log | 0.75 | 12 | 0.2376 | 0.3126 | 0.2374 | | No log | 0.875 | 14 | 0.2395 | 0.3156 | 0.2394 | | No log | 1.0 | 16 | 0.2207 | 0.3200 | 0.2206 | | No log | 1.125 | 18 | 0.2110 | 0.3141 | 0.2108 | | No log | 1.25 | 20 | 0.2044 | 0.3240 | 0.2042 | | No log | 1.375 | 22 | 0.1940 | 0.3474 | 0.1939 | | No log | 1.5 | 24 | 0.1935 | 0.3423 | 0.1934 | | No log | 1.625 | 26 | 0.1971 | 0.3465 | 0.1970 | | No log | 1.75 | 28 | 0.1987 | 0.3444 | 0.1987 | | No log | 1.875 | 30 | 0.1940 | 0.3650 | 0.1939 | | No log | 2.0 | 32 | 0.1935 | 0.3667 | 0.1934 | | No log | 2.125 | 34 | 0.1905 | 0.3581 | 0.1903 | | No log | 2.25 | 36 | 0.1874 | 0.3617 | 0.1872 | | No log | 2.375 | 38 | 0.1955 | 0.3549 | 0.1954 | | No log | 2.5 | 40 | 0.1888 | 0.3513 | 0.1887 | | No log | 2.625 | 42 | 0.1910 | 0.3504 | 0.1908 | | No log | 2.75 | 44 | 0.1989 | 0.3557 | 0.1987 | | No log | 2.875 | 46 | 0.1822 | 0.3658 | 0.1820 | | No log | 3.0 | 48 | 0.1794 | 0.3695 | 0.1792 | | No log | 3.125 | 50 | 0.1806 | 0.3586 | 0.1804 | | No log | 3.25 | 52 | 0.1801 | 0.3642 | 0.1799 | | No log | 3.375 | 54 | 0.1932 | 0.3566 | 0.1930 | | No log | 3.5 | 56 | 0.1965 | 0.3665 | 0.1964 | | No log | 3.625 | 58 | 0.1835 | 0.3933 | 0.1832 | | No log | 3.75 | 60 | 0.1823 | 0.4014 | 0.1821 | | No log | 3.875 | 62 | 0.1810 | 0.3904 | 0.1808 | | No log | 4.0 | 64 | 0.1812 | 0.3641 | 0.1809 | | No log | 4.125 | 66 | 0.1872 | 0.3508 | 0.1869 | | No log | 4.25 | 68 | 0.1876 | 0.3444 | 0.1873 | | No log | 4.375 | 70 | 0.1871 | 0.3465 | 0.1869 | | No log | 4.5 | 72 | 0.1839 | 0.3476 | 0.1836 | | No log | 4.625 | 74 | 0.1851 | 0.3502 | 0.1848 | | No log | 4.75 | 76 | 0.1995 | 0.3556 | 0.1992 | | No log | 4.875 | 78 | 0.2297 | 0.3406 | 0.2295 | | No log | 5.0 | 80 | 0.2197 | 0.3527 | 0.2195 | | No log | 5.125 | 82 | 0.2076 | 0.3687 | 0.2074 | | No log | 5.25 | 84 | 0.2032 | 0.3594 | 0.2029 | | No log | 5.375 | 86 | 0.1949 | 0.3789 | 0.1946 | | No log | 5.5 | 88 | 0.1891 | 0.3720 | 0.1888 | | No log | 5.625 | 90 | 0.1897 | 0.3616 | 0.1894 | | No log | 5.75 | 92 | 0.2058 | 0.3531 | 0.2054 | | No log | 5.875 | 94 | 0.2551 | 0.3116 | 0.2547 | | No log | 6.0 | 96 | 0.2912 | 0.2956 | 0.2910 | | No log | 6.125 | 98 | 0.2694 | 0.3103 | 0.2690 | | No log | 6.25 | 100 | 0.2180 | 0.3539 | 0.2176 | | No log | 6.375 | 102 | 0.1895 | 0.3898 | 0.1891 | | No log | 6.5 | 104 | 0.1849 | 0.3916 | 0.1845 | | No log | 6.625 | 106 | 0.1941 | 0.3673 | 0.1936 | | No log | 6.75 | 108 | 0.2121 | 0.3477 | 0.2117 | | No log | 6.875 | 110 | 0.2249 | 0.3320 | 0.2245 | | No log | 7.0 | 112 | 0.2260 | 0.3320 | 0.2256 | | No log | 7.125 | 114 | 0.2089 | 0.3539 | 0.2085 | | No log | 7.25 | 116 | 0.1910 | 0.3665 | 0.1905 | | No log | 7.375 | 118 | 0.1866 | 0.3736 | 0.1861 | | No log | 7.5 | 120 | 0.1896 | 0.3689 | 0.1891 | | No log | 7.625 | 122 | 0.2002 | 0.3543 | 0.1997 | | No log | 7.75 | 124 | 0.2193 | 0.3459 | 0.2188 | | No log | 7.875 | 126 | 0.2204 | 0.3441 | 0.2200 | | No log | 8.0 | 128 | 0.2176 | 0.3432 | 0.2171 | | No log | 8.125 | 130 | 0.2102 | 0.3423 | 0.2097 | | No log | 8.25 | 132 | 0.2052 | 0.3459 | 0.2046 | | No log | 8.375 | 134 | 0.1977 | 0.3634 | 0.1972 | | No log | 8.5 | 136 | 0.1998 | 0.3555 | 0.1993 | | No log | 8.625 | 138 | 0.2030 | 0.3505 | 0.2024 | | No log | 8.75 | 140 | 0.2003 | 0.3581 | 0.1998 | | No log | 8.875 | 142 | 0.2002 | 0.3589 | 0.1996 | | No log | 9.0 | 144 | 0.2005 | 0.3559 | 0.2000 | | No log | 9.125 | 146 | 0.2054 | 0.3522 | 0.2048 | | No log | 9.25 | 148 | 0.2092 | 0.3477 | 0.2086 | | No log | 9.375 | 150 | 0.2149 | 0.3495 | 0.2144 | | No log | 9.5 | 152 | 0.2218 | 0.3503 | 0.2213 | | No log | 9.625 | 154 | 0.2252 | 0.3503 | 0.2246 | | No log | 9.75 | 156 | 0.2286 | 0.3459 | 0.2280 | | No log | 9.875 | 158 | 0.2281 | 0.3459 | 0.2276 | | No log | 10.0 | 160 | 0.2278 | 0.3503 | 0.2272 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1