--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task2_fold6 results: [] --- # arabert_cross_relevance_task2_fold6 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: 0.5925 - Qwk: 0.1247 - Mse: 0.5913 ## 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 | 1.0484 | 0.0144 | 1.0495 | | No log | 0.25 | 4 | 0.4722 | 0.0661 | 0.4712 | | No log | 0.375 | 6 | 0.3587 | 0.0337 | 0.3586 | | No log | 0.5 | 8 | 0.3104 | 0.0426 | 0.3106 | | No log | 0.625 | 10 | 0.3347 | 0.1842 | 0.3346 | | No log | 0.75 | 12 | 0.4174 | 0.1571 | 0.4170 | | No log | 0.875 | 14 | 0.3844 | 0.2015 | 0.3843 | | No log | 1.0 | 16 | 0.2810 | 0.2211 | 0.2812 | | No log | 1.125 | 18 | 0.2939 | 0.2330 | 0.2941 | | No log | 1.25 | 20 | 0.3046 | 0.2330 | 0.3047 | | No log | 1.375 | 22 | 0.2859 | 0.2445 | 0.2860 | | No log | 1.5 | 24 | 0.2753 | 0.2406 | 0.2755 | | No log | 1.625 | 26 | 0.2512 | 0.2194 | 0.2515 | | No log | 1.75 | 28 | 0.2794 | 0.2445 | 0.2795 | | No log | 1.875 | 30 | 0.3449 | 0.2103 | 0.3448 | | No log | 2.0 | 32 | 0.3052 | 0.2252 | 0.3052 | | No log | 2.125 | 34 | 0.2622 | 0.2406 | 0.2624 | | No log | 2.25 | 36 | 0.2752 | 0.2445 | 0.2754 | | No log | 2.375 | 38 | 0.3529 | 0.2096 | 0.3530 | | No log | 2.5 | 40 | 0.3863 | 0.2053 | 0.3862 | | No log | 2.625 | 42 | 0.3238 | 0.2239 | 0.3238 | | No log | 2.75 | 44 | 0.2611 | 0.2325 | 0.2612 | | No log | 2.875 | 46 | 0.2541 | 0.2194 | 0.2540 | | No log | 3.0 | 48 | 0.2822 | 0.2224 | 0.2820 | | No log | 3.125 | 50 | 0.3796 | 0.2141 | 0.3790 | | No log | 3.25 | 52 | 0.4184 | 0.1975 | 0.4178 | | No log | 3.375 | 54 | 0.3500 | 0.2226 | 0.3497 | | No log | 3.5 | 56 | 0.2922 | 0.2252 | 0.2922 | | No log | 3.625 | 58 | 0.3018 | 0.2200 | 0.3019 | | No log | 3.75 | 60 | 0.3826 | 0.2125 | 0.3825 | | No log | 3.875 | 62 | 0.4484 | 0.2078 | 0.4482 | | No log | 4.0 | 64 | 0.4422 | 0.1971 | 0.4419 | | No log | 4.125 | 66 | 0.4471 | 0.1900 | 0.4468 | | No log | 4.25 | 68 | 0.3883 | 0.2089 | 0.3881 | | No log | 4.375 | 70 | 0.3712 | 0.2053 | 0.3709 | | No log | 4.5 | 72 | 0.4054 | 0.2125 | 0.4050 | | No log | 4.625 | 74 | 0.4224 | 0.1935 | 0.4219 | | No log | 4.75 | 76 | 0.4248 | 0.2008 | 0.4243 | | No log | 4.875 | 78 | 0.4469 | 0.1830 | 0.4463 | | No log | 5.0 | 80 | 0.5131 | 0.1339 | 0.5123 | | No log | 5.125 | 82 | 0.5222 | 0.1283 | 0.5214 | | No log | 5.25 | 84 | 0.5110 | 0.1302 | 0.5102 | | No log | 5.375 | 86 | 0.4800 | 0.1441 | 0.4793 | | No log | 5.5 | 88 | 0.4837 | 0.1503 | 0.4829 | | No log | 5.625 | 90 | 0.5706 | 0.1391 | 0.5695 | | No log | 5.75 | 92 | 0.6503 | 0.0885 | 0.6490 | | No log | 5.875 | 94 | 0.6117 | 0.1127 | 0.6104 | | No log | 6.0 | 96 | 0.5654 | 0.1391 | 0.5642 | | No log | 6.125 | 98 | 0.5250 | 0.1527 | 0.5240 | | No log | 6.25 | 100 | 0.5182 | 0.1469 | 0.5172 | | No log | 6.375 | 102 | 0.5641 | 0.1230 | 0.5630 | | No log | 6.5 | 104 | 0.6136 | 0.0980 | 0.6124 | | No log | 6.625 | 106 | 0.5738 | 0.1178 | 0.5727 | | No log | 6.75 | 108 | 0.5142 | 0.1455 | 0.5133 | | No log | 6.875 | 110 | 0.5024 | 0.1441 | 0.5015 | | No log | 7.0 | 112 | 0.5299 | 0.1360 | 0.5289 | | No log | 7.125 | 114 | 0.5277 | 0.1322 | 0.5267 | | No log | 7.25 | 116 | 0.5830 | 0.1356 | 0.5818 | | No log | 7.375 | 118 | 0.6347 | 0.1213 | 0.6334 | | No log | 7.5 | 120 | 0.6357 | 0.1162 | 0.6344 | | No log | 7.625 | 122 | 0.5716 | 0.1320 | 0.5704 | | No log | 7.75 | 124 | 0.5196 | 0.1381 | 0.5186 | | No log | 7.875 | 126 | 0.4886 | 0.1528 | 0.4877 | | No log | 8.0 | 128 | 0.4936 | 0.1503 | 0.4927 | | No log | 8.125 | 130 | 0.5221 | 0.1576 | 0.5212 | | No log | 8.25 | 132 | 0.5852 | 0.1247 | 0.5841 | | No log | 8.375 | 134 | 0.6353 | 0.0968 | 0.6341 | | No log | 8.5 | 136 | 0.6372 | 0.0968 | 0.6360 | | No log | 8.625 | 138 | 0.6395 | 0.0968 | 0.6383 | | No log | 8.75 | 140 | 0.6416 | 0.0968 | 0.6403 | | No log | 8.875 | 142 | 0.6267 | 0.1112 | 0.6254 | | No log | 9.0 | 144 | 0.5882 | 0.1211 | 0.5871 | | No log | 9.125 | 146 | 0.5690 | 0.1320 | 0.5679 | | No log | 9.25 | 148 | 0.5639 | 0.1376 | 0.5629 | | No log | 9.375 | 150 | 0.5739 | 0.1265 | 0.5728 | | No log | 9.5 | 152 | 0.5772 | 0.1265 | 0.5761 | | No log | 9.625 | 154 | 0.5840 | 0.1247 | 0.5828 | | No log | 9.75 | 156 | 0.5884 | 0.1247 | 0.5873 | | No log | 9.875 | 158 | 0.5912 | 0.1247 | 0.5900 | | No log | 10.0 | 160 | 0.5925 | 0.1247 | 0.5913 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1