--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task5_fold2 results: [] --- # arabert_cross_organization_task5_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: 1.1250 - Qwk: 0.0300 - Mse: 1.1225 ## 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 | 4.8650 | -0.0023 | 4.8621 | | No log | 0.25 | 4 | 2.3813 | 0.0030 | 2.3764 | | No log | 0.375 | 6 | 0.8965 | 0.0095 | 0.8941 | | No log | 0.5 | 8 | 0.8278 | 0.0983 | 0.8251 | | No log | 0.625 | 10 | 0.8457 | 0.0276 | 0.8417 | | No log | 0.75 | 12 | 0.9196 | 0.0618 | 0.9166 | | No log | 0.875 | 14 | 1.0317 | -0.0899 | 1.0303 | | No log | 1.0 | 16 | 1.1713 | 0.0 | 1.1691 | | No log | 1.125 | 18 | 1.2251 | 0.0 | 1.2227 | | No log | 1.25 | 20 | 1.3511 | 0.0 | 1.3490 | | No log | 1.375 | 22 | 1.2633 | -0.0232 | 1.2615 | | No log | 1.5 | 24 | 1.3009 | 0.0 | 1.2985 | | No log | 1.625 | 26 | 1.1982 | 0.0182 | 1.1952 | | No log | 1.75 | 28 | 1.0708 | 0.0333 | 1.0677 | | No log | 1.875 | 30 | 1.0776 | 0.0360 | 1.0747 | | No log | 2.0 | 32 | 1.0691 | 0.0333 | 1.0663 | | No log | 2.125 | 34 | 1.0114 | 0.0253 | 1.0084 | | No log | 2.25 | 36 | 1.0232 | 0.0710 | 1.0205 | | No log | 2.375 | 38 | 1.0445 | 0.0155 | 1.0419 | | No log | 2.5 | 40 | 1.0455 | 0.0680 | 1.0427 | | No log | 2.625 | 42 | 1.1297 | 0.0680 | 1.1268 | | No log | 2.75 | 44 | 1.2353 | 0.0333 | 1.2324 | | No log | 2.875 | 46 | 1.0593 | 0.0176 | 1.0562 | | No log | 3.0 | 48 | 1.0440 | 0.0424 | 1.0409 | | No log | 3.125 | 50 | 1.1623 | 0.0360 | 1.1594 | | No log | 3.25 | 52 | 1.2841 | 0.0 | 1.2814 | | No log | 3.375 | 54 | 1.1945 | 0.0 | 1.1918 | | No log | 3.5 | 56 | 0.9910 | 0.0680 | 0.9881 | | No log | 3.625 | 58 | 1.0024 | 0.0397 | 0.9994 | | No log | 3.75 | 60 | 1.2429 | 0.0360 | 1.2400 | | No log | 3.875 | 62 | 1.4419 | 0.0226 | 1.4390 | | No log | 4.0 | 64 | 1.4478 | 0.0750 | 1.4448 | | No log | 4.125 | 66 | 1.2244 | 0.0740 | 1.2215 | | No log | 4.25 | 68 | 1.1031 | 0.0416 | 1.1002 | | No log | 4.375 | 70 | 1.1904 | 0.0710 | 1.1876 | | No log | 4.5 | 72 | 1.3453 | 0.0182 | 1.3428 | | No log | 4.625 | 74 | 1.3082 | 0.0 | 1.3057 | | No log | 4.75 | 76 | 1.1660 | 0.0565 | 1.1633 | | No log | 4.875 | 78 | 1.0042 | 0.0424 | 1.0013 | | No log | 5.0 | 80 | 0.9419 | 0.1245 | 0.9389 | | No log | 5.125 | 82 | 1.0260 | 0.0680 | 1.0232 | | No log | 5.25 | 84 | 1.1655 | 0.0388 | 1.1629 | | No log | 5.375 | 86 | 1.2867 | 0.0 | 1.2843 | | No log | 5.5 | 88 | 1.3234 | 0.0025 | 1.3209 | | No log | 5.625 | 90 | 1.2955 | 0.0182 | 1.2928 | | No log | 5.75 | 92 | 1.1588 | 0.0536 | 1.1559 | | No log | 5.875 | 94 | 1.1432 | 0.0536 | 1.1403 | | No log | 6.0 | 96 | 1.1569 | 0.0536 | 1.1542 | | No log | 6.125 | 98 | 1.0621 | 0.0536 | 1.0594 | | No log | 6.25 | 100 | 1.0340 | 0.1214 | 1.0312 | | No log | 6.375 | 102 | 1.0071 | 0.0789 | 1.0043 | | No log | 6.5 | 104 | 1.0650 | 0.0849 | 1.0622 | | No log | 6.625 | 106 | 1.1044 | 0.0536 | 1.1017 | | No log | 6.75 | 108 | 1.0963 | 0.0536 | 1.0936 | | No log | 6.875 | 110 | 1.0911 | 0.0279 | 1.0883 | | No log | 7.0 | 112 | 1.0569 | 0.0789 | 1.0542 | | No log | 7.125 | 114 | 1.0545 | 0.0789 | 1.0517 | | No log | 7.25 | 116 | 1.0799 | 0.1081 | 1.0772 | | No log | 7.375 | 118 | 1.1261 | 0.0536 | 1.1234 | | No log | 7.5 | 120 | 1.1714 | 0.0536 | 1.1688 | | No log | 7.625 | 122 | 1.1479 | 0.0508 | 1.1451 | | No log | 7.75 | 124 | 1.0979 | 0.0424 | 1.0951 | | No log | 7.875 | 126 | 1.0280 | 0.0789 | 1.0252 | | No log | 8.0 | 128 | 1.0373 | 0.0622 | 1.0347 | | No log | 8.125 | 130 | 1.0287 | 0.0650 | 1.0261 | | No log | 8.25 | 132 | 1.0350 | 0.0650 | 1.0325 | | No log | 8.375 | 134 | 1.0478 | 0.0650 | 1.0452 | | No log | 8.5 | 136 | 1.0550 | 0.0650 | 1.0524 | | No log | 8.625 | 138 | 1.0875 | 0.0880 | 1.0848 | | No log | 8.75 | 140 | 1.1279 | 0.0279 | 1.1252 | | No log | 8.875 | 142 | 1.1587 | 0.0326 | 1.1561 | | No log | 9.0 | 144 | 1.1762 | 0.0326 | 1.1736 | | No log | 9.125 | 146 | 1.1639 | 0.0326 | 1.1613 | | No log | 9.25 | 148 | 1.1345 | 0.0300 | 1.1319 | | No log | 9.375 | 150 | 1.1260 | 0.0300 | 1.1233 | | No log | 9.5 | 152 | 1.1247 | 0.0300 | 1.1221 | | No log | 9.625 | 154 | 1.1251 | 0.0300 | 1.1225 | | No log | 9.75 | 156 | 1.1248 | 0.0300 | 1.1223 | | No log | 9.875 | 158 | 1.1243 | 0.0300 | 1.1218 | | No log | 10.0 | 160 | 1.1250 | 0.0300 | 1.1225 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1