--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task2_fold2 results: [] --- # arabert_cross_organization_task2_fold2 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: 1.0548 - Qwk: 0.1458 - Mse: 1.0548 ## 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 | 4.4485 | -0.0131 | 4.4485 | | No log | 0.2353 | 4 | 1.8009 | -0.0153 | 1.8009 | | No log | 0.3529 | 6 | 1.1944 | 0.0437 | 1.1944 | | No log | 0.4706 | 8 | 1.2459 | -0.0439 | 1.2459 | | No log | 0.5882 | 10 | 1.1688 | -0.0450 | 1.1688 | | No log | 0.7059 | 12 | 1.1521 | 0.0379 | 1.1521 | | No log | 0.8235 | 14 | 1.1603 | -0.0096 | 1.1603 | | No log | 0.9412 | 16 | 1.1948 | -0.0723 | 1.1948 | | No log | 1.0588 | 18 | 1.3189 | -0.0617 | 1.3189 | | No log | 1.1765 | 20 | 1.4608 | -0.0017 | 1.4608 | | No log | 1.2941 | 22 | 1.2409 | -0.0661 | 1.2409 | | No log | 1.4118 | 24 | 1.1260 | 0.0513 | 1.1260 | | No log | 1.5294 | 26 | 1.1582 | 0.0639 | 1.1582 | | No log | 1.6471 | 28 | 1.1974 | -0.0637 | 1.1974 | | No log | 1.7647 | 30 | 1.2427 | -0.0072 | 1.2427 | | No log | 1.8824 | 32 | 1.2670 | -0.0237 | 1.2670 | | No log | 2.0 | 34 | 1.2862 | -0.0775 | 1.2862 | | No log | 2.1176 | 36 | 1.2811 | -0.0301 | 1.2811 | | No log | 2.2353 | 38 | 1.2493 | 0.0198 | 1.2493 | | No log | 2.3529 | 40 | 1.3023 | -0.0524 | 1.3023 | | No log | 2.4706 | 42 | 1.1620 | 0.0963 | 1.1620 | | No log | 2.5882 | 44 | 1.2006 | 0.0203 | 1.2006 | | No log | 2.7059 | 46 | 1.1721 | -0.0203 | 1.1721 | | No log | 2.8235 | 48 | 1.1251 | 0.0909 | 1.1251 | | No log | 2.9412 | 50 | 1.1646 | 0.0614 | 1.1646 | | No log | 3.0588 | 52 | 1.1537 | 0.1100 | 1.1537 | | No log | 3.1765 | 54 | 1.1619 | 0.0397 | 1.1619 | | No log | 3.2941 | 56 | 1.1446 | 0.0356 | 1.1446 | | No log | 3.4118 | 58 | 1.1100 | 0.1366 | 1.1100 | | No log | 3.5294 | 60 | 1.0950 | 0.0927 | 1.0950 | | No log | 3.6471 | 62 | 1.1914 | 0.0668 | 1.1914 | | No log | 3.7647 | 64 | 1.1642 | 0.0734 | 1.1642 | | No log | 3.8824 | 66 | 1.0702 | 0.1452 | 1.0702 | | No log | 4.0 | 68 | 1.0704 | 0.1474 | 1.0704 | | No log | 4.1176 | 70 | 1.1170 | 0.0391 | 1.1170 | | No log | 4.2353 | 72 | 1.1800 | 0.0595 | 1.1800 | | No log | 4.3529 | 74 | 1.0993 | 0.1283 | 1.0993 | | No log | 4.4706 | 76 | 1.1934 | -0.0135 | 1.1934 | | No log | 4.5882 | 78 | 1.3754 | -0.0259 | 1.3754 | | No log | 4.7059 | 80 | 1.2204 | -0.0135 | 1.2204 | | No log | 4.8235 | 82 | 1.1114 | 0.1016 | 1.1114 | | No log | 4.9412 | 84 | 1.3701 | 0.0289 | 1.3701 | | No log | 5.0588 | 86 | 1.3316 | 0.0728 | 1.3316 | | No log | 5.1765 | 88 | 1.0952 | 0.1185 | 1.0952 | | No log | 5.2941 | 90 | 1.1314 | 0.0453 | 1.1314 | | No log | 5.4118 | 92 | 1.2064 | -0.0035 | 1.2064 | | No log | 5.5294 | 94 | 1.1624 | 0.0524 | 1.1624 | | No log | 5.6471 | 96 | 1.0616 | 0.1805 | 1.0616 | | No log | 5.7647 | 98 | 1.0707 | 0.1579 | 1.0707 | | No log | 5.8824 | 100 | 1.0682 | 0.1543 | 1.0682 | | No log | 6.0 | 102 | 1.0755 | 0.1611 | 1.0755 | | No log | 6.1176 | 104 | 1.1047 | 0.1146 | 1.1047 | | No log | 6.2353 | 106 | 1.0839 | 0.1630 | 1.0839 | | No log | 6.3529 | 108 | 1.1070 | 0.1144 | 1.1070 | | No log | 6.4706 | 110 | 1.1227 | 0.1144 | 1.1227 | | No log | 6.5882 | 112 | 1.1078 | 0.1050 | 1.1078 | | No log | 6.7059 | 114 | 1.1016 | 0.1871 | 1.1016 | | No log | 6.8235 | 116 | 1.0973 | 0.1835 | 1.0973 | | No log | 6.9412 | 118 | 1.0879 | 0.1622 | 1.0879 | | No log | 7.0588 | 120 | 1.1030 | 0.1077 | 1.1030 | | No log | 7.1765 | 122 | 1.0923 | 0.1497 | 1.0923 | | No log | 7.2941 | 124 | 1.0894 | 0.1520 | 1.0894 | | No log | 7.4118 | 126 | 1.0755 | 0.1253 | 1.0755 | | No log | 7.5294 | 128 | 1.0677 | 0.1253 | 1.0677 | | No log | 7.6471 | 130 | 1.0610 | 0.1520 | 1.0610 | | No log | 7.7647 | 132 | 1.1106 | 0.0794 | 1.1106 | | No log | 7.8824 | 134 | 1.0932 | 0.0888 | 1.0932 | | No log | 8.0 | 136 | 1.0392 | 0.1335 | 1.0392 | | No log | 8.1176 | 138 | 1.0756 | 0.1295 | 1.0756 | | No log | 8.2353 | 140 | 1.1032 | 0.1371 | 1.1032 | | No log | 8.3529 | 142 | 1.0707 | 0.1344 | 1.0707 | | No log | 8.4706 | 144 | 1.0399 | 0.1754 | 1.0399 | | No log | 8.5882 | 146 | 1.0486 | 0.1205 | 1.0486 | | No log | 8.7059 | 148 | 1.0606 | 0.1379 | 1.0606 | | No log | 8.8235 | 150 | 1.0717 | 0.1241 | 1.0717 | | No log | 8.9412 | 152 | 1.0674 | 0.1379 | 1.0674 | | No log | 9.0588 | 154 | 1.0527 | 0.1066 | 1.0527 | | No log | 9.1765 | 156 | 1.0449 | 0.1458 | 1.0449 | | No log | 9.2941 | 158 | 1.0540 | 0.1907 | 1.0540 | | No log | 9.4118 | 160 | 1.0626 | 0.1548 | 1.0626 | | No log | 9.5294 | 162 | 1.0605 | 0.1577 | 1.0605 | | No log | 9.6471 | 164 | 1.0583 | 0.1605 | 1.0583 | | No log | 9.7647 | 166 | 1.0560 | 0.1458 | 1.0560 | | No log | 9.8824 | 168 | 1.0549 | 0.1458 | 1.0549 | | No log | 10.0 | 170 | 1.0548 | 0.1458 | 1.0548 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1