--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task1_fold5 results: [] --- # arabert_cross_relevance_task1_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: 0.1878 - Qwk: 0.3819 - Mse: 0.1876 ## 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 | 0.1333 | 2 | 0.4109 | 0.2336 | 0.4106 | | No log | 0.2667 | 4 | 0.3205 | 0.4919 | 0.3198 | | No log | 0.4 | 6 | 0.3796 | 0.1681 | 0.3786 | | No log | 0.5333 | 8 | 0.4000 | 0.1674 | 0.3992 | | No log | 0.6667 | 10 | 0.3695 | 0.3199 | 0.3690 | | No log | 0.8 | 12 | 0.2845 | 0.3350 | 0.2841 | | No log | 0.9333 | 14 | 0.2416 | 0.3864 | 0.2408 | | No log | 1.0667 | 16 | 0.3319 | 0.5930 | 0.3309 | | No log | 1.2 | 18 | 0.2997 | 0.5123 | 0.2988 | | No log | 1.3333 | 20 | 0.2367 | 0.2937 | 0.2361 | | No log | 1.4667 | 22 | 0.2587 | 0.3126 | 0.2583 | | No log | 1.6 | 24 | 0.2424 | 0.3355 | 0.2423 | | No log | 1.7333 | 26 | 0.2050 | 0.3596 | 0.2050 | | No log | 1.8667 | 28 | 0.1955 | 0.4152 | 0.1955 | | No log | 2.0 | 30 | 0.2132 | 0.4904 | 0.2130 | | No log | 2.1333 | 32 | 0.2250 | 0.4135 | 0.2247 | | No log | 2.2667 | 34 | 0.2143 | 0.3443 | 0.2140 | | No log | 2.4 | 36 | 0.1969 | 0.3501 | 0.1967 | | No log | 2.5333 | 38 | 0.1788 | 0.3703 | 0.1787 | | No log | 2.6667 | 40 | 0.1794 | 0.3757 | 0.1792 | | No log | 2.8 | 42 | 0.1996 | 0.3852 | 0.1993 | | No log | 2.9333 | 44 | 0.2126 | 0.3724 | 0.2122 | | No log | 3.0667 | 46 | 0.2175 | 0.3534 | 0.2172 | | No log | 3.2 | 48 | 0.1984 | 0.3771 | 0.1982 | | No log | 3.3333 | 50 | 0.1905 | 0.3695 | 0.1903 | | No log | 3.4667 | 52 | 0.1879 | 0.3695 | 0.1877 | | No log | 3.6 | 54 | 0.1891 | 0.3766 | 0.1889 | | No log | 3.7333 | 56 | 0.1833 | 0.4205 | 0.1831 | | No log | 3.8667 | 58 | 0.1756 | 0.3942 | 0.1755 | | No log | 4.0 | 60 | 0.1782 | 0.3642 | 0.1782 | | No log | 4.1333 | 62 | 0.1748 | 0.3617 | 0.1748 | | No log | 4.2667 | 64 | 0.1775 | 0.3736 | 0.1774 | | No log | 4.4 | 66 | 0.1912 | 0.3958 | 0.1910 | | No log | 4.5333 | 68 | 0.2067 | 0.3725 | 0.2064 | | No log | 4.6667 | 70 | 0.1994 | 0.3983 | 0.1991 | | No log | 4.8 | 72 | 0.1917 | 0.4319 | 0.1914 | | No log | 4.9333 | 74 | 0.1976 | 0.4129 | 0.1976 | | No log | 5.0667 | 76 | 0.2040 | 0.4133 | 0.2040 | | No log | 5.2 | 78 | 0.1996 | 0.3886 | 0.1996 | | No log | 5.3333 | 80 | 0.1919 | 0.3944 | 0.1917 | | No log | 5.4667 | 82 | 0.2038 | 0.3686 | 0.2035 | | No log | 5.6 | 84 | 0.2110 | 0.3572 | 0.2107 | | No log | 5.7333 | 86 | 0.2060 | 0.3677 | 0.2058 | | No log | 5.8667 | 88 | 0.1924 | 0.3835 | 0.1922 | | No log | 6.0 | 90 | 0.1834 | 0.4065 | 0.1833 | | No log | 6.1333 | 92 | 0.1793 | 0.4025 | 0.1792 | | No log | 6.2667 | 94 | 0.1797 | 0.4067 | 0.1796 | | No log | 6.4 | 96 | 0.1838 | 0.3854 | 0.1837 | | No log | 6.5333 | 98 | 0.1902 | 0.3712 | 0.1900 | | No log | 6.6667 | 100 | 0.1977 | 0.3732 | 0.1975 | | No log | 6.8 | 102 | 0.1991 | 0.3668 | 0.1989 | | No log | 6.9333 | 104 | 0.1975 | 0.3732 | 0.1973 | | No log | 7.0667 | 106 | 0.1963 | 0.3677 | 0.1961 | | No log | 7.2 | 108 | 0.1964 | 0.3641 | 0.1962 | | No log | 7.3333 | 110 | 0.1928 | 0.3659 | 0.1926 | | No log | 7.4667 | 112 | 0.1906 | 0.3765 | 0.1905 | | No log | 7.6 | 114 | 0.1938 | 0.3804 | 0.1936 | | No log | 7.7333 | 116 | 0.1973 | 0.3852 | 0.1971 | | No log | 7.8667 | 118 | 0.2049 | 0.3790 | 0.2047 | | No log | 8.0 | 120 | 0.2071 | 0.3725 | 0.2069 | | No log | 8.1333 | 122 | 0.2054 | 0.3763 | 0.2051 | | No log | 8.2667 | 124 | 0.2031 | 0.3715 | 0.2028 | | No log | 8.4 | 126 | 0.2018 | 0.3547 | 0.2016 | | No log | 8.5333 | 128 | 0.2011 | 0.3501 | 0.2009 | | No log | 8.6667 | 130 | 0.2020 | 0.3532 | 0.2018 | | No log | 8.8 | 132 | 0.2004 | 0.3532 | 0.2002 | | No log | 8.9333 | 134 | 0.1983 | 0.3587 | 0.1982 | | No log | 9.0667 | 136 | 0.1957 | 0.3632 | 0.1955 | | No log | 9.2 | 138 | 0.1933 | 0.3632 | 0.1931 | | No log | 9.3333 | 140 | 0.1911 | 0.3749 | 0.1909 | | No log | 9.4667 | 142 | 0.1894 | 0.3819 | 0.1893 | | No log | 9.6 | 144 | 0.1885 | 0.3819 | 0.1883 | | No log | 9.7333 | 146 | 0.1879 | 0.3819 | 0.1878 | | No log | 9.8667 | 148 | 0.1877 | 0.3819 | 0.1876 | | No log | 10.0 | 150 | 0.1878 | 0.3819 | 0.1876 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1