--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_organization_task4_fold3 results: [] --- # arabert_cross_organization_task4_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: 0.5515 - Qwk: 0.8285 - Mse: 0.5515 ## 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 | 1.8640 | 0.0713 | 1.8640 | | No log | 0.2353 | 4 | 1.2390 | 0.2961 | 1.2390 | | No log | 0.3529 | 6 | 1.0659 | 0.5023 | 1.0659 | | No log | 0.4706 | 8 | 0.7195 | 0.6388 | 0.7195 | | No log | 0.5882 | 10 | 0.6736 | 0.6636 | 0.6736 | | No log | 0.7059 | 12 | 0.6560 | 0.7539 | 0.6560 | | No log | 0.8235 | 14 | 0.6088 | 0.7149 | 0.6088 | | No log | 0.9412 | 16 | 0.5695 | 0.7426 | 0.5695 | | No log | 1.0588 | 18 | 0.5646 | 0.7706 | 0.5646 | | No log | 1.1765 | 20 | 0.5616 | 0.7796 | 0.5616 | | No log | 1.2941 | 22 | 0.5516 | 0.7811 | 0.5516 | | No log | 1.4118 | 24 | 0.5475 | 0.7868 | 0.5475 | | No log | 1.5294 | 26 | 0.5246 | 0.7436 | 0.5246 | | No log | 1.6471 | 28 | 0.5463 | 0.6820 | 0.5463 | | No log | 1.7647 | 30 | 0.5511 | 0.7714 | 0.5511 | | No log | 1.8824 | 32 | 0.6634 | 0.7890 | 0.6634 | | No log | 2.0 | 34 | 0.5815 | 0.7811 | 0.5815 | | No log | 2.1176 | 36 | 0.5186 | 0.7320 | 0.5186 | | No log | 2.2353 | 38 | 0.5161 | 0.7348 | 0.5161 | | No log | 2.3529 | 40 | 0.5145 | 0.7637 | 0.5145 | | No log | 2.4706 | 42 | 0.5367 | 0.7805 | 0.5367 | | No log | 2.5882 | 44 | 0.5238 | 0.7807 | 0.5238 | | No log | 2.7059 | 46 | 0.5169 | 0.7771 | 0.5169 | | No log | 2.8235 | 48 | 0.5287 | 0.7852 | 0.5287 | | No log | 2.9412 | 50 | 0.5446 | 0.7867 | 0.5446 | | No log | 3.0588 | 52 | 0.5892 | 0.7786 | 0.5892 | | No log | 3.1765 | 54 | 0.5913 | 0.7818 | 0.5913 | | No log | 3.2941 | 56 | 0.5352 | 0.7813 | 0.5352 | | No log | 3.4118 | 58 | 0.5197 | 0.7785 | 0.5197 | | No log | 3.5294 | 60 | 0.5895 | 0.7951 | 0.5895 | | No log | 3.6471 | 62 | 0.6125 | 0.7950 | 0.6125 | | No log | 3.7647 | 64 | 0.5768 | 0.7875 | 0.5768 | | No log | 3.8824 | 66 | 0.5110 | 0.7717 | 0.5110 | | No log | 4.0 | 68 | 0.5375 | 0.7910 | 0.5375 | | No log | 4.1176 | 70 | 0.6011 | 0.7996 | 0.6011 | | No log | 4.2353 | 72 | 0.5525 | 0.7824 | 0.5525 | | No log | 4.3529 | 74 | 0.5620 | 0.7907 | 0.5620 | | No log | 4.4706 | 76 | 0.5220 | 0.7908 | 0.5220 | | No log | 4.5882 | 78 | 0.5028 | 0.7641 | 0.5028 | | No log | 4.7059 | 80 | 0.5102 | 0.7841 | 0.5102 | | No log | 4.8235 | 82 | 0.6101 | 0.8166 | 0.6101 | | No log | 4.9412 | 84 | 0.7637 | 0.8377 | 0.7637 | | No log | 5.0588 | 86 | 0.6895 | 0.8271 | 0.6895 | | No log | 5.1765 | 88 | 0.5154 | 0.7893 | 0.5154 | | No log | 5.2941 | 90 | 0.4808 | 0.7932 | 0.4808 | | No log | 5.4118 | 92 | 0.5241 | 0.7847 | 0.5241 | | No log | 5.5294 | 94 | 0.6303 | 0.8282 | 0.6303 | | No log | 5.6471 | 96 | 0.6026 | 0.8213 | 0.6026 | | No log | 5.7647 | 98 | 0.5078 | 0.8217 | 0.5078 | | No log | 5.8824 | 100 | 0.4940 | 0.8070 | 0.4940 | | No log | 6.0 | 102 | 0.5633 | 0.8182 | 0.5633 | | No log | 6.1176 | 104 | 0.7172 | 0.8375 | 0.7172 | | No log | 6.2353 | 106 | 0.7195 | 0.8305 | 0.7195 | | No log | 6.3529 | 108 | 0.5965 | 0.8196 | 0.5965 | | No log | 6.4706 | 110 | 0.5114 | 0.7928 | 0.5114 | | No log | 6.5882 | 112 | 0.5064 | 0.7886 | 0.5064 | | No log | 6.7059 | 114 | 0.5439 | 0.8123 | 0.5439 | | No log | 6.8235 | 116 | 0.6118 | 0.8257 | 0.6118 | | No log | 6.9412 | 118 | 0.6143 | 0.8179 | 0.6143 | | No log | 7.0588 | 120 | 0.6140 | 0.8174 | 0.6140 | | No log | 7.1765 | 122 | 0.5766 | 0.8207 | 0.5766 | | No log | 7.2941 | 124 | 0.5369 | 0.8188 | 0.5369 | | No log | 7.4118 | 126 | 0.5480 | 0.8132 | 0.5480 | | No log | 7.5294 | 128 | 0.6078 | 0.8236 | 0.6078 | | No log | 7.6471 | 130 | 0.6701 | 0.8235 | 0.6701 | | No log | 7.7647 | 132 | 0.6414 | 0.8221 | 0.6414 | | No log | 7.8824 | 134 | 0.5864 | 0.8195 | 0.5864 | | No log | 8.0 | 136 | 0.5473 | 0.8186 | 0.5473 | | No log | 8.1176 | 138 | 0.5345 | 0.8188 | 0.5345 | | No log | 8.2353 | 140 | 0.5432 | 0.8202 | 0.5432 | | No log | 8.3529 | 142 | 0.5420 | 0.8239 | 0.5420 | | No log | 8.4706 | 144 | 0.5381 | 0.8188 | 0.5381 | | No log | 8.5882 | 146 | 0.5139 | 0.8016 | 0.5139 | | No log | 8.7059 | 148 | 0.5052 | 0.7981 | 0.5052 | | No log | 8.8235 | 150 | 0.5095 | 0.7948 | 0.5095 | | No log | 8.9412 | 152 | 0.5334 | 0.8173 | 0.5334 | | No log | 9.0588 | 154 | 0.5783 | 0.8340 | 0.5783 | | No log | 9.1765 | 156 | 0.6036 | 0.8366 | 0.6036 | | No log | 9.2941 | 158 | 0.6056 | 0.8403 | 0.6056 | | No log | 9.4118 | 160 | 0.5911 | 0.8320 | 0.5911 | | No log | 9.5294 | 162 | 0.5683 | 0.8301 | 0.5683 | | No log | 9.6471 | 164 | 0.5583 | 0.8287 | 0.5583 | | No log | 9.7647 | 166 | 0.5530 | 0.8269 | 0.5530 | | No log | 9.8824 | 168 | 0.5512 | 0.8285 | 0.5512 | | No log | 10.0 | 170 | 0.5515 | 0.8285 | 0.5515 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1