--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task3_fold3 results: [] --- # arabert_cross_organization_task3_fold3 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: 0.5370 - Qwk: 0.7944 - Mse: 0.5370 ## 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 | 1.7580 | 0.0890 | 1.7580 | | No log | 0.25 | 4 | 1.2272 | 0.4035 | 1.2272 | | No log | 0.375 | 6 | 0.9464 | 0.5403 | 0.9464 | | No log | 0.5 | 8 | 0.7613 | 0.6565 | 0.7613 | | No log | 0.625 | 10 | 0.6541 | 0.7029 | 0.6541 | | No log | 0.75 | 12 | 0.6490 | 0.7391 | 0.6490 | | No log | 0.875 | 14 | 0.7327 | 0.7661 | 0.7327 | | No log | 1.0 | 16 | 0.5927 | 0.6919 | 0.5927 | | No log | 1.125 | 18 | 0.5964 | 0.6599 | 0.5964 | | No log | 1.25 | 20 | 0.6354 | 0.7806 | 0.6354 | | No log | 1.375 | 22 | 0.8402 | 0.7721 | 0.8402 | | No log | 1.5 | 24 | 0.6567 | 0.7904 | 0.6567 | | No log | 1.625 | 26 | 0.5279 | 0.7541 | 0.5279 | | No log | 1.75 | 28 | 0.5231 | 0.7390 | 0.5231 | | No log | 1.875 | 30 | 0.5289 | 0.7813 | 0.5289 | | No log | 2.0 | 32 | 0.5925 | 0.7797 | 0.5925 | | No log | 2.125 | 34 | 0.5332 | 0.7806 | 0.5332 | | No log | 2.25 | 36 | 0.5328 | 0.7818 | 0.5328 | | No log | 2.375 | 38 | 0.5917 | 0.7871 | 0.5917 | | No log | 2.5 | 40 | 0.5461 | 0.7940 | 0.5461 | | No log | 2.625 | 42 | 0.5813 | 0.7869 | 0.5813 | | No log | 2.75 | 44 | 0.5361 | 0.7835 | 0.5361 | | No log | 2.875 | 46 | 0.4895 | 0.7367 | 0.4895 | | No log | 3.0 | 48 | 0.4986 | 0.7699 | 0.4986 | | No log | 3.125 | 50 | 0.5492 | 0.7845 | 0.5492 | | No log | 3.25 | 52 | 0.6585 | 0.7981 | 0.6585 | | No log | 3.375 | 54 | 0.5821 | 0.7973 | 0.5821 | | No log | 3.5 | 56 | 0.4999 | 0.7692 | 0.4999 | | No log | 3.625 | 58 | 0.5101 | 0.7700 | 0.5101 | | No log | 3.75 | 60 | 0.5803 | 0.7877 | 0.5803 | | No log | 3.875 | 62 | 0.5825 | 0.78 | 0.5825 | | No log | 4.0 | 64 | 0.5152 | 0.7826 | 0.5152 | | No log | 4.125 | 66 | 0.5153 | 0.7737 | 0.5153 | | No log | 4.25 | 68 | 0.5298 | 0.7824 | 0.5298 | | No log | 4.375 | 70 | 0.4955 | 0.7601 | 0.4955 | | No log | 4.5 | 72 | 0.5345 | 0.7834 | 0.5345 | | No log | 4.625 | 74 | 0.5955 | 0.7877 | 0.5955 | | No log | 4.75 | 76 | 0.5233 | 0.7839 | 0.5233 | | No log | 4.875 | 78 | 0.4939 | 0.7760 | 0.4939 | | No log | 5.0 | 80 | 0.4893 | 0.7615 | 0.4893 | | No log | 5.125 | 82 | 0.5115 | 0.7835 | 0.5115 | | No log | 5.25 | 84 | 0.5169 | 0.7812 | 0.5169 | | No log | 5.375 | 86 | 0.5423 | 0.7856 | 0.5423 | | No log | 5.5 | 88 | 0.5269 | 0.7741 | 0.5269 | | No log | 5.625 | 90 | 0.5073 | 0.7634 | 0.5073 | | No log | 5.75 | 92 | 0.5209 | 0.7721 | 0.5209 | | No log | 5.875 | 94 | 0.6436 | 0.8138 | 0.6436 | | No log | 6.0 | 96 | 0.7068 | 0.8088 | 0.7068 | | No log | 6.125 | 98 | 0.6021 | 0.7992 | 0.6021 | | No log | 6.25 | 100 | 0.5022 | 0.7464 | 0.5022 | | No log | 6.375 | 102 | 0.4976 | 0.7471 | 0.4976 | | No log | 6.5 | 104 | 0.5144 | 0.7552 | 0.5144 | | No log | 6.625 | 106 | 0.5770 | 0.7931 | 0.5770 | | No log | 6.75 | 108 | 0.5866 | 0.7931 | 0.5866 | | No log | 6.875 | 110 | 0.5239 | 0.7649 | 0.5239 | | No log | 7.0 | 112 | 0.4930 | 0.7531 | 0.4930 | | No log | 7.125 | 114 | 0.4884 | 0.7636 | 0.4884 | | No log | 7.25 | 116 | 0.5129 | 0.7744 | 0.5129 | | No log | 7.375 | 118 | 0.5771 | 0.7982 | 0.5771 | | No log | 7.5 | 120 | 0.5703 | 0.7982 | 0.5703 | | No log | 7.625 | 122 | 0.5147 | 0.7681 | 0.5147 | | No log | 7.75 | 124 | 0.4973 | 0.7739 | 0.4973 | | No log | 7.875 | 126 | 0.4888 | 0.7760 | 0.4888 | | No log | 8.0 | 128 | 0.5035 | 0.7817 | 0.5035 | | No log | 8.125 | 130 | 0.5124 | 0.7723 | 0.5124 | | No log | 8.25 | 132 | 0.5107 | 0.7782 | 0.5107 | | No log | 8.375 | 134 | 0.5195 | 0.7768 | 0.5195 | | No log | 8.5 | 136 | 0.5271 | 0.7724 | 0.5271 | | No log | 8.625 | 138 | 0.5365 | 0.7820 | 0.5365 | | No log | 8.75 | 140 | 0.5329 | 0.7862 | 0.5329 | | No log | 8.875 | 142 | 0.5215 | 0.7883 | 0.5215 | | No log | 9.0 | 144 | 0.5191 | 0.7827 | 0.5191 | | No log | 9.125 | 146 | 0.5120 | 0.7830 | 0.5120 | | No log | 9.25 | 148 | 0.5044 | 0.7814 | 0.5044 | | No log | 9.375 | 150 | 0.5086 | 0.7870 | 0.5086 | | No log | 9.5 | 152 | 0.5195 | 0.7956 | 0.5195 | | No log | 9.625 | 154 | 0.5294 | 0.7955 | 0.5294 | | No log | 9.75 | 156 | 0.5377 | 0.7944 | 0.5377 | | No log | 9.875 | 158 | 0.5380 | 0.7958 | 0.5380 | | No log | 10.0 | 160 | 0.5370 | 0.7944 | 0.5370 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1