--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task6_fold2 results: [] --- # arabert_cross_organization_task6_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: 1.0752 - Qwk: 0.1211 - Mse: 1.0727 ## 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 | 3.7816 | 0.0007 | 3.7767 | | No log | 0.2353 | 4 | 1.3542 | 0.0008 | 1.3493 | | No log | 0.3529 | 6 | 0.8381 | 0.0381 | 0.8355 | | No log | 0.4706 | 8 | 0.8831 | -0.0815 | 0.8796 | | No log | 0.5882 | 10 | 0.8969 | 0.0429 | 0.8931 | | No log | 0.7059 | 12 | 0.8250 | 0.0520 | 0.8218 | | No log | 0.8235 | 14 | 1.0019 | 0.0182 | 0.9999 | | No log | 0.9412 | 16 | 1.1717 | -0.0025 | 1.1701 | | No log | 1.0588 | 18 | 1.2136 | -0.0025 | 1.2120 | | No log | 1.1765 | 20 | 1.1606 | 0.0 | 1.1587 | | No log | 1.2941 | 22 | 1.2446 | 0.0 | 1.2426 | | No log | 1.4118 | 24 | 1.3967 | 0.0 | 1.3948 | | No log | 1.5294 | 26 | 1.4847 | 0.0253 | 1.4827 | | No log | 1.6471 | 28 | 1.3244 | 0.0231 | 1.3221 | | No log | 1.7647 | 30 | 1.0785 | 0.0360 | 1.0760 | | No log | 1.8824 | 32 | 0.8498 | 0.1972 | 0.8470 | | No log | 2.0 | 34 | 0.9134 | 0.1247 | 0.9107 | | No log | 2.1176 | 36 | 1.1156 | 0.0182 | 1.1130 | | No log | 2.2353 | 38 | 1.0973 | 0.0 | 1.0948 | | No log | 2.3529 | 40 | 1.0822 | 0.0182 | 1.0794 | | No log | 2.4706 | 42 | 1.0078 | 0.0789 | 1.0047 | | No log | 2.5882 | 44 | 1.1175 | 0.0880 | 1.1144 | | No log | 2.7059 | 46 | 1.3284 | 0.0465 | 1.3253 | | No log | 2.8235 | 48 | 1.6008 | 0.0931 | 1.5976 | | No log | 2.9412 | 50 | 2.1079 | 0.0276 | 2.1049 | | No log | 3.0588 | 52 | 2.2734 | 0.0412 | 2.2705 | | No log | 3.1765 | 54 | 1.8347 | 0.1369 | 1.8320 | | No log | 3.2941 | 56 | 1.3122 | 0.0884 | 1.3096 | | No log | 3.4118 | 58 | 1.2595 | 0.0664 | 1.2569 | | No log | 3.5294 | 60 | 1.4282 | 0.1006 | 1.4256 | | No log | 3.6471 | 62 | 1.5462 | 0.1413 | 1.5436 | | No log | 3.7647 | 64 | 1.3829 | 0.0593 | 1.3803 | | No log | 3.8824 | 66 | 0.9939 | 0.1230 | 0.9914 | | No log | 4.0 | 68 | 0.8054 | 0.1788 | 0.8030 | | No log | 4.1176 | 70 | 0.7868 | 0.1816 | 0.7845 | | No log | 4.2353 | 72 | 0.9015 | 0.1607 | 0.8991 | | No log | 4.3529 | 74 | 1.2405 | 0.0483 | 1.2379 | | No log | 4.4706 | 76 | 1.4275 | 0.0040 | 1.4247 | | No log | 4.5882 | 78 | 1.3885 | 0.0201 | 1.3856 | | No log | 4.7059 | 80 | 1.2664 | 0.0431 | 1.2634 | | No log | 4.8235 | 82 | 1.0916 | 0.0750 | 1.0885 | | No log | 4.9412 | 84 | 1.0885 | 0.0159 | 1.0854 | | No log | 5.0588 | 86 | 1.1736 | 0.0869 | 1.1705 | | No log | 5.1765 | 88 | 1.3914 | 0.1105 | 1.3885 | | No log | 5.2941 | 90 | 1.5037 | 0.0839 | 1.5010 | | No log | 5.4118 | 92 | 1.4052 | 0.0391 | 1.4026 | | No log | 5.5294 | 94 | 1.2441 | 0.0662 | 1.2417 | | No log | 5.6471 | 96 | 1.1952 | 0.0646 | 1.1929 | | No log | 5.7647 | 98 | 1.1442 | 0.0814 | 1.1419 | | No log | 5.8824 | 100 | 1.1950 | 0.0855 | 1.1926 | | No log | 6.0 | 102 | 1.3191 | 0.0880 | 1.3167 | | No log | 6.1176 | 104 | 1.4094 | 0.0999 | 1.4070 | | No log | 6.2353 | 106 | 1.2755 | 0.1507 | 1.2730 | | No log | 6.3529 | 108 | 1.0797 | 0.1262 | 1.0770 | | No log | 6.4706 | 110 | 0.9830 | 0.1381 | 0.9804 | | No log | 6.5882 | 112 | 0.9647 | 0.1405 | 0.9620 | | No log | 6.7059 | 114 | 1.0370 | 0.1146 | 1.0345 | | No log | 6.8235 | 116 | 1.1227 | 0.0885 | 1.1203 | | No log | 6.9412 | 118 | 1.2057 | 0.1026 | 1.2033 | | No log | 7.0588 | 120 | 1.2261 | 0.0518 | 1.2238 | | No log | 7.1765 | 122 | 1.2047 | 0.0652 | 1.2023 | | No log | 7.2941 | 124 | 1.0652 | 0.1195 | 1.0628 | | No log | 7.4118 | 126 | 0.9603 | 0.1804 | 0.9578 | | No log | 7.5294 | 128 | 0.9421 | 0.1812 | 0.9395 | | No log | 7.6471 | 130 | 1.0068 | 0.1111 | 1.0041 | | No log | 7.7647 | 132 | 1.1676 | 0.1367 | 1.1650 | | No log | 7.8824 | 134 | 1.3081 | 0.1382 | 1.3055 | | No log | 8.0 | 136 | 1.3954 | 0.1123 | 1.3929 | | No log | 8.1176 | 138 | 1.3854 | 0.1123 | 1.3829 | | No log | 8.2353 | 140 | 1.2987 | 0.1203 | 1.2962 | | No log | 8.3529 | 142 | 1.1429 | 0.1190 | 1.1405 | | No log | 8.4706 | 144 | 1.0515 | 0.1232 | 1.0491 | | No log | 8.5882 | 146 | 1.0416 | 0.1371 | 1.0392 | | No log | 8.7059 | 148 | 1.0625 | 0.1438 | 1.0601 | | No log | 8.8235 | 150 | 1.0904 | 0.1152 | 1.0880 | | No log | 8.9412 | 152 | 1.1358 | 0.1190 | 1.1334 | | No log | 9.0588 | 154 | 1.1786 | 0.1043 | 1.1762 | | No log | 9.1765 | 156 | 1.1978 | 0.1043 | 1.1954 | | No log | 9.2941 | 158 | 1.1835 | 0.1043 | 1.1810 | | No log | 9.4118 | 160 | 1.1423 | 0.1190 | 1.1399 | | No log | 9.5294 | 162 | 1.1135 | 0.1336 | 1.1110 | | No log | 9.6471 | 164 | 1.1006 | 0.1132 | 1.0981 | | No log | 9.7647 | 166 | 1.0926 | 0.1277 | 1.0902 | | No log | 9.8824 | 168 | 1.0805 | 0.1211 | 1.0780 | | No log | 10.0 | 170 | 1.0752 | 0.1211 | 1.0727 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1