--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task1_fold1 results: [] --- # arabert_cross_organization_task1_fold1 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: 0.9947 - Qwk: 0.0679 - Mse: 0.9916 ## 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 | 5.2049 | -0.0008 | 5.2020 | | No log | 0.25 | 4 | 1.9284 | -0.0122 | 1.9256 | | No log | 0.375 | 6 | 1.0209 | 0.0513 | 1.0167 | | No log | 0.5 | 8 | 0.8405 | 0.0824 | 0.8373 | | No log | 0.625 | 10 | 0.8656 | 0.1060 | 0.8628 | | No log | 0.75 | 12 | 0.8332 | 0.1240 | 0.8306 | | No log | 0.875 | 14 | 0.8775 | 0.0730 | 0.8754 | | No log | 1.0 | 16 | 0.9183 | 0.0104 | 0.9162 | | No log | 1.125 | 18 | 0.9057 | 0.0508 | 0.9032 | | No log | 1.25 | 20 | 0.8886 | 0.1273 | 0.8859 | | No log | 1.375 | 22 | 0.9957 | 0.0849 | 0.9930 | | No log | 1.5 | 24 | 1.0595 | 0.1181 | 1.0564 | | No log | 1.625 | 26 | 1.2289 | 0.0182 | 1.2258 | | No log | 1.75 | 28 | 1.2976 | 0.0182 | 1.2948 | | No log | 1.875 | 30 | 0.9648 | 0.1402 | 0.9617 | | No log | 2.0 | 32 | 0.9714 | 0.1016 | 0.9684 | | No log | 2.125 | 34 | 0.9511 | 0.0710 | 0.9483 | | No log | 2.25 | 36 | 0.8591 | 0.1425 | 0.8564 | | No log | 2.375 | 38 | 0.8696 | 0.1182 | 0.8667 | | No log | 2.5 | 40 | 1.0662 | 0.0360 | 1.0635 | | No log | 2.625 | 42 | 1.1724 | 0.0360 | 1.1696 | | No log | 2.75 | 44 | 1.3100 | 0.0182 | 1.3071 | | No log | 2.875 | 46 | 1.3304 | 0.0182 | 1.3275 | | No log | 3.0 | 48 | 1.0676 | 0.0424 | 1.0645 | | No log | 3.125 | 50 | 0.9732 | 0.0668 | 0.9701 | | No log | 3.25 | 52 | 1.1173 | 0.0279 | 1.1143 | | No log | 3.375 | 54 | 1.2420 | 0.0182 | 1.2393 | | No log | 3.5 | 56 | 1.1410 | 0.0155 | 1.1382 | | No log | 3.625 | 58 | 0.9316 | 0.0268 | 0.9285 | | No log | 3.75 | 60 | 0.8907 | 0.1122 | 0.8876 | | No log | 3.875 | 62 | 1.0183 | 0.0253 | 1.0153 | | No log | 4.0 | 64 | 1.1271 | 0.0279 | 1.1242 | | No log | 4.125 | 66 | 1.1742 | 0.0300 | 1.1712 | | No log | 4.25 | 68 | 1.2066 | 0.0682 | 1.2034 | | No log | 4.375 | 70 | 1.2604 | 0.0377 | 1.2572 | | No log | 4.5 | 72 | 1.1679 | 0.0830 | 1.1646 | | No log | 4.625 | 74 | 1.1770 | 0.0966 | 1.1739 | | No log | 4.75 | 76 | 1.1163 | 0.0966 | 1.1131 | | No log | 4.875 | 78 | 0.9754 | 0.0695 | 0.9721 | | No log | 5.0 | 80 | 0.9489 | 0.0767 | 0.9456 | | No log | 5.125 | 82 | 0.9900 | 0.0994 | 0.9868 | | No log | 5.25 | 84 | 0.8622 | 0.0654 | 0.8588 | | No log | 5.375 | 86 | 0.8621 | 0.1028 | 0.8586 | | No log | 5.5 | 88 | 1.0043 | 0.0807 | 1.0011 | | No log | 5.625 | 90 | 1.0565 | 0.0448 | 1.0533 | | No log | 5.75 | 92 | 0.9899 | 0.0848 | 0.9866 | | No log | 5.875 | 94 | 1.1141 | 0.0466 | 1.1111 | | No log | 6.0 | 96 | 1.3040 | 0.0906 | 1.3012 | | No log | 6.125 | 98 | 1.2856 | 0.1112 | 1.2829 | | No log | 6.25 | 100 | 1.3671 | 0.0962 | 1.3644 | | No log | 6.375 | 102 | 1.2601 | 0.1091 | 1.2574 | | No log | 6.5 | 104 | 1.2039 | 0.1595 | 1.2011 | | No log | 6.625 | 106 | 1.1272 | 0.0913 | 1.1244 | | No log | 6.75 | 108 | 1.0754 | 0.0958 | 1.0725 | | No log | 6.875 | 110 | 1.0818 | 0.0777 | 1.0790 | | No log | 7.0 | 112 | 1.0175 | 0.0670 | 1.0146 | | No log | 7.125 | 114 | 0.9552 | 0.0569 | 0.9521 | | No log | 7.25 | 116 | 0.8938 | 0.1278 | 0.8906 | | No log | 7.375 | 118 | 0.9486 | 0.0697 | 0.9455 | | No log | 7.5 | 120 | 0.9351 | 0.0773 | 0.9319 | | No log | 7.625 | 122 | 0.8928 | 0.0870 | 0.8895 | | No log | 7.75 | 124 | 0.8558 | 0.1373 | 0.8524 | | No log | 7.875 | 126 | 0.8561 | 0.1606 | 0.8527 | | No log | 8.0 | 128 | 0.9205 | 0.0389 | 0.9174 | | No log | 8.125 | 130 | 1.0514 | 0.0941 | 1.0484 | | No log | 8.25 | 132 | 1.0795 | 0.1246 | 1.0765 | | No log | 8.375 | 134 | 1.0151 | 0.0977 | 1.0120 | | No log | 8.5 | 136 | 0.9815 | 0.0716 | 0.9784 | | No log | 8.625 | 138 | 0.9817 | 0.0668 | 0.9786 | | No log | 8.75 | 140 | 0.9721 | 0.0597 | 0.9690 | | No log | 8.875 | 142 | 0.9865 | 0.0668 | 0.9834 | | No log | 9.0 | 144 | 0.9956 | 0.0716 | 0.9925 | | No log | 9.125 | 146 | 0.9824 | 0.0807 | 0.9793 | | No log | 9.25 | 148 | 0.9599 | 0.0721 | 0.9568 | | No log | 9.375 | 150 | 0.9488 | 0.0858 | 0.9456 | | No log | 9.5 | 152 | 0.9443 | 0.0858 | 0.9411 | | No log | 9.625 | 154 | 0.9603 | 0.0721 | 0.9572 | | No log | 9.75 | 156 | 0.9767 | 0.0770 | 0.9735 | | No log | 9.875 | 158 | 0.9906 | 0.0679 | 0.9874 | | No log | 10.0 | 160 | 0.9947 | 0.0679 | 0.9916 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1