--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task5_fold4 results: [] --- # arabert_cross_organization_task5_fold4 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: 0.4286 - Qwk: 0.7401 - Mse: 0.4286 ## 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 | 1.9126 | 0.0900 | 1.9126 | | No log | 0.25 | 4 | 1.3553 | 0.0025 | 1.3553 | | No log | 0.375 | 6 | 1.0461 | 0.3696 | 1.0461 | | No log | 0.5 | 8 | 0.7260 | 0.5218 | 0.7260 | | No log | 0.625 | 10 | 0.6063 | 0.5755 | 0.6063 | | No log | 0.75 | 12 | 0.6127 | 0.7262 | 0.6127 | | No log | 0.875 | 14 | 0.6736 | 0.7318 | 0.6736 | | No log | 1.0 | 16 | 0.5956 | 0.6135 | 0.5956 | | No log | 1.125 | 18 | 0.5532 | 0.5825 | 0.5532 | | No log | 1.25 | 20 | 0.5116 | 0.5953 | 0.5116 | | No log | 1.375 | 22 | 0.5776 | 0.7239 | 0.5776 | | No log | 1.5 | 24 | 0.5445 | 0.7456 | 0.5445 | | No log | 1.625 | 26 | 0.5385 | 0.7516 | 0.5385 | | No log | 1.75 | 28 | 0.4556 | 0.7391 | 0.4556 | | No log | 1.875 | 30 | 0.4530 | 0.7546 | 0.4530 | | No log | 2.0 | 32 | 0.4987 | 0.7575 | 0.4987 | | No log | 2.125 | 34 | 0.4840 | 0.7553 | 0.4840 | | No log | 2.25 | 36 | 0.4749 | 0.7522 | 0.4749 | | No log | 2.375 | 38 | 0.3991 | 0.7577 | 0.3991 | | No log | 2.5 | 40 | 0.3891 | 0.7567 | 0.3891 | | No log | 2.625 | 42 | 0.5607 | 0.7796 | 0.5607 | | No log | 2.75 | 44 | 0.6672 | 0.7717 | 0.6672 | | No log | 2.875 | 46 | 0.4754 | 0.7796 | 0.4754 | | No log | 3.0 | 48 | 0.4533 | 0.6964 | 0.4533 | | No log | 3.125 | 50 | 0.4390 | 0.7211 | 0.4390 | | No log | 3.25 | 52 | 0.4645 | 0.7813 | 0.4645 | | No log | 3.375 | 54 | 0.5369 | 0.7841 | 0.5369 | | No log | 3.5 | 56 | 0.4539 | 0.7751 | 0.4539 | | No log | 3.625 | 58 | 0.3966 | 0.7289 | 0.3966 | | No log | 3.75 | 60 | 0.3996 | 0.7120 | 0.3996 | | No log | 3.875 | 62 | 0.4091 | 0.7331 | 0.4091 | | No log | 4.0 | 64 | 0.4476 | 0.7566 | 0.4476 | | No log | 4.125 | 66 | 0.5300 | 0.7780 | 0.5300 | | No log | 4.25 | 68 | 0.5160 | 0.7858 | 0.5160 | | No log | 4.375 | 70 | 0.4266 | 0.7744 | 0.4266 | | No log | 4.5 | 72 | 0.3914 | 0.7537 | 0.3914 | | No log | 4.625 | 74 | 0.4220 | 0.7523 | 0.4220 | | No log | 4.75 | 76 | 0.4624 | 0.7629 | 0.4624 | | No log | 4.875 | 78 | 0.4224 | 0.7701 | 0.4224 | | No log | 5.0 | 80 | 0.3791 | 0.7493 | 0.3791 | | No log | 5.125 | 82 | 0.3895 | 0.7222 | 0.3895 | | No log | 5.25 | 84 | 0.3859 | 0.7449 | 0.3859 | | No log | 5.375 | 86 | 0.4706 | 0.7869 | 0.4706 | | No log | 5.5 | 88 | 0.5223 | 0.7814 | 0.5223 | | No log | 5.625 | 90 | 0.4664 | 0.7791 | 0.4664 | | No log | 5.75 | 92 | 0.4027 | 0.7311 | 0.4027 | | No log | 5.875 | 94 | 0.4225 | 0.6937 | 0.4225 | | No log | 6.0 | 96 | 0.4142 | 0.6982 | 0.4142 | | No log | 6.125 | 98 | 0.4140 | 0.7389 | 0.4140 | | No log | 6.25 | 100 | 0.4989 | 0.7642 | 0.4989 | | No log | 6.375 | 102 | 0.6033 | 0.7735 | 0.6033 | | No log | 6.5 | 104 | 0.5857 | 0.7770 | 0.5857 | | No log | 6.625 | 106 | 0.4835 | 0.7720 | 0.4835 | | No log | 6.75 | 108 | 0.4292 | 0.7392 | 0.4292 | | No log | 6.875 | 110 | 0.4236 | 0.7113 | 0.4236 | | No log | 7.0 | 112 | 0.4315 | 0.7304 | 0.4315 | | No log | 7.125 | 114 | 0.4781 | 0.7663 | 0.4781 | | No log | 7.25 | 116 | 0.5131 | 0.7782 | 0.5131 | | No log | 7.375 | 118 | 0.4884 | 0.7743 | 0.4884 | | No log | 7.5 | 120 | 0.4351 | 0.7513 | 0.4351 | | No log | 7.625 | 122 | 0.4135 | 0.7412 | 0.4135 | | No log | 7.75 | 124 | 0.4144 | 0.7379 | 0.4144 | | No log | 7.875 | 126 | 0.4260 | 0.7560 | 0.4260 | | No log | 8.0 | 128 | 0.4698 | 0.7681 | 0.4698 | | No log | 8.125 | 130 | 0.5081 | 0.8027 | 0.5081 | | No log | 8.25 | 132 | 0.5012 | 0.8033 | 0.5012 | | No log | 8.375 | 134 | 0.4563 | 0.7630 | 0.4563 | | No log | 8.5 | 136 | 0.4233 | 0.7367 | 0.4233 | | No log | 8.625 | 138 | 0.4146 | 0.7168 | 0.4146 | | No log | 8.75 | 140 | 0.4102 | 0.7219 | 0.4102 | | No log | 8.875 | 142 | 0.4038 | 0.7250 | 0.4038 | | No log | 9.0 | 144 | 0.4045 | 0.7339 | 0.4045 | | No log | 9.125 | 146 | 0.4174 | 0.7425 | 0.4174 | | No log | 9.25 | 148 | 0.4352 | 0.7626 | 0.4352 | | No log | 9.375 | 150 | 0.4412 | 0.7624 | 0.4412 | | No log | 9.5 | 152 | 0.4385 | 0.7588 | 0.4385 | | No log | 9.625 | 154 | 0.4340 | 0.7458 | 0.4340 | | No log | 9.75 | 156 | 0.4311 | 0.7401 | 0.4311 | | No log | 9.875 | 158 | 0.4286 | 0.7401 | 0.4286 | | No log | 10.0 | 160 | 0.4286 | 0.7401 | 0.4286 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1