--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task7_fold3 results: [] --- # arabert_cross_organization_task7_fold3 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: 1.2477 - Qwk: 0.0397 - Mse: 1.2477 ## 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 | 0.1176 | 2 | 4.6630 | -0.0214 | 4.6630 | | No log | 0.2353 | 4 | 1.9131 | -0.0296 | 1.9131 | | No log | 0.3529 | 6 | 1.4779 | 0.0333 | 1.4779 | | No log | 0.4706 | 8 | 1.3898 | -0.0031 | 1.3898 | | No log | 0.5882 | 10 | 1.1632 | -0.0182 | 1.1632 | | No log | 0.7059 | 12 | 1.2046 | 0.0046 | 1.2046 | | No log | 0.8235 | 14 | 1.1480 | -0.0723 | 1.1480 | | No log | 0.9412 | 16 | 1.1436 | -0.0110 | 1.1436 | | No log | 1.0588 | 18 | 1.1619 | -0.0110 | 1.1619 | | No log | 1.1765 | 20 | 1.1482 | -0.0110 | 1.1482 | | No log | 1.2941 | 22 | 1.1202 | -0.0110 | 1.1202 | | No log | 1.4118 | 24 | 1.1170 | 0.0062 | 1.1170 | | No log | 1.5294 | 26 | 1.1174 | 0.0413 | 1.1174 | | No log | 1.6471 | 28 | 1.1486 | -0.0248 | 1.1486 | | No log | 1.7647 | 30 | 1.2697 | 0.0 | 1.2697 | | No log | 1.8824 | 32 | 1.2498 | -0.0147 | 1.2498 | | No log | 2.0 | 34 | 1.1692 | -0.0248 | 1.1692 | | No log | 2.1176 | 36 | 1.1913 | -0.0203 | 1.1913 | | No log | 2.2353 | 38 | 1.2360 | -0.0255 | 1.2360 | | No log | 2.3529 | 40 | 1.1562 | -0.0046 | 1.1562 | | No log | 2.4706 | 42 | 1.1715 | -0.0074 | 1.1715 | | No log | 2.5882 | 44 | 1.2562 | -0.0147 | 1.2562 | | No log | 2.7059 | 46 | 1.1883 | -0.0039 | 1.1883 | | No log | 2.8235 | 48 | 1.1458 | 0.0518 | 1.1458 | | No log | 2.9412 | 50 | 1.2475 | -0.0289 | 1.2475 | | No log | 3.0588 | 52 | 1.3234 | 0.0059 | 1.3234 | | No log | 3.1765 | 54 | 1.1838 | -0.0002 | 1.1838 | | No log | 3.2941 | 56 | 1.1405 | 0.0753 | 1.1405 | | No log | 3.4118 | 58 | 1.1817 | 0.0686 | 1.1817 | | No log | 3.5294 | 60 | 1.1663 | 0.0753 | 1.1663 | | No log | 3.6471 | 62 | 1.1574 | 0.0944 | 1.1574 | | No log | 3.7647 | 64 | 1.1895 | 0.0474 | 1.1895 | | No log | 3.8824 | 66 | 1.1771 | 0.0160 | 1.1771 | | No log | 4.0 | 68 | 1.1811 | 0.0725 | 1.1811 | | No log | 4.1176 | 70 | 1.2361 | 0.0469 | 1.2361 | | No log | 4.2353 | 72 | 1.2386 | 0.0650 | 1.2386 | | No log | 4.3529 | 74 | 1.1740 | 0.1183 | 1.1740 | | No log | 4.4706 | 76 | 1.1578 | 0.1142 | 1.1578 | | No log | 4.5882 | 78 | 1.1478 | 0.0927 | 1.1478 | | No log | 4.7059 | 80 | 1.1556 | 0.0890 | 1.1556 | | No log | 4.8235 | 82 | 1.1743 | 0.0682 | 1.1743 | | No log | 4.9412 | 84 | 1.1621 | 0.0682 | 1.1621 | | No log | 5.0588 | 86 | 1.1329 | 0.0963 | 1.1329 | | No log | 5.1765 | 88 | 1.1322 | 0.1113 | 1.1322 | | No log | 5.2941 | 90 | 1.1440 | 0.1234 | 1.1440 | | No log | 5.4118 | 92 | 1.2118 | 0.0376 | 1.2118 | | No log | 5.5294 | 94 | 1.2862 | 0.0713 | 1.2862 | | No log | 5.6471 | 96 | 1.3217 | 0.0599 | 1.3217 | | No log | 5.7647 | 98 | 1.2121 | 0.0624 | 1.2121 | | No log | 5.8824 | 100 | 1.1592 | 0.1501 | 1.1592 | | No log | 6.0 | 102 | 1.1912 | 0.0385 | 1.1912 | | No log | 6.1176 | 104 | 1.1673 | 0.0828 | 1.1673 | | No log | 6.2353 | 106 | 1.1644 | 0.0448 | 1.1644 | | No log | 6.3529 | 108 | 1.2438 | 0.0629 | 1.2438 | | No log | 6.4706 | 110 | 1.3083 | 0.0622 | 1.3083 | | No log | 6.5882 | 112 | 1.2970 | 0.0470 | 1.2970 | | No log | 6.7059 | 114 | 1.2160 | 0.0295 | 1.2160 | | No log | 6.8235 | 116 | 1.1682 | 0.0881 | 1.1682 | | No log | 6.9412 | 118 | 1.1659 | 0.0898 | 1.1659 | | No log | 7.0588 | 120 | 1.1694 | 0.1029 | 1.1694 | | No log | 7.1765 | 122 | 1.1813 | 0.0829 | 1.1813 | | No log | 7.2941 | 124 | 1.1840 | 0.0847 | 1.1840 | | No log | 7.4118 | 126 | 1.1941 | 0.0847 | 1.1941 | | No log | 7.5294 | 128 | 1.2296 | 0.0915 | 1.2296 | | No log | 7.6471 | 130 | 1.2731 | 0.0561 | 1.2731 | | No log | 7.7647 | 132 | 1.2863 | 0.0680 | 1.2863 | | No log | 7.8824 | 134 | 1.2644 | 0.0391 | 1.2644 | | No log | 8.0 | 136 | 1.2471 | 0.0771 | 1.2471 | | No log | 8.1176 | 138 | 1.2423 | 0.0789 | 1.2423 | | No log | 8.2353 | 140 | 1.2401 | 0.0596 | 1.2401 | | No log | 8.3529 | 142 | 1.2475 | 0.0596 | 1.2475 | | No log | 8.4706 | 144 | 1.2539 | 0.0703 | 1.2539 | | No log | 8.5882 | 146 | 1.2593 | 0.0794 | 1.2593 | | No log | 8.7059 | 148 | 1.2770 | 0.0551 | 1.2770 | | No log | 8.8235 | 150 | 1.2937 | 0.0858 | 1.2937 | | No log | 8.9412 | 152 | 1.2970 | 0.0840 | 1.2970 | | No log | 9.0588 | 154 | 1.3005 | 0.0657 | 1.3005 | | No log | 9.1765 | 156 | 1.2860 | 0.0657 | 1.2860 | | No log | 9.2941 | 158 | 1.2799 | 0.0355 | 1.2799 | | No log | 9.4118 | 160 | 1.2697 | 0.0407 | 1.2697 | | No log | 9.5294 | 162 | 1.2616 | 0.0653 | 1.2616 | | No log | 9.6471 | 164 | 1.2564 | 0.0374 | 1.2564 | | No log | 9.7647 | 166 | 1.2527 | 0.0397 | 1.2527 | | No log | 9.8824 | 168 | 1.2493 | 0.0397 | 1.2493 | | No log | 10.0 | 170 | 1.2477 | 0.0397 | 1.2477 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1