--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task1_fold2 results: [] --- # arabert_cross_relevance_task1_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: 0.4917 - Qwk: -0.0345 - Mse: 0.4917 ## 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 | 0.5402 | 0.0504 | 0.5402 | | No log | 0.2353 | 4 | 0.5522 | 0.1129 | 0.5522 | | No log | 0.3529 | 6 | 0.4760 | 0.1129 | 0.4760 | | No log | 0.4706 | 8 | 0.2772 | 0.0 | 0.2772 | | No log | 0.5882 | 10 | 0.2693 | 0.0 | 0.2693 | | No log | 0.7059 | 12 | 0.2659 | -0.0235 | 0.2659 | | No log | 0.8235 | 14 | 0.3218 | -0.0448 | 0.3218 | | No log | 0.9412 | 16 | 0.3400 | -0.1260 | 0.3400 | | No log | 1.0588 | 18 | 0.3031 | -0.0764 | 0.3031 | | No log | 1.1765 | 20 | 0.3006 | -0.0235 | 0.3006 | | No log | 1.2941 | 22 | 0.3269 | 0.0 | 0.3269 | | No log | 1.4118 | 24 | 0.3005 | 0.0 | 0.3005 | | No log | 1.5294 | 26 | 0.2883 | -0.0374 | 0.2883 | | No log | 1.6471 | 28 | 0.3040 | -0.0764 | 0.3040 | | No log | 1.7647 | 30 | 0.2964 | -0.0374 | 0.2964 | | No log | 1.8824 | 32 | 0.2940 | -0.0235 | 0.2940 | | No log | 2.0 | 34 | 0.2905 | -0.0473 | 0.2905 | | No log | 2.1176 | 36 | 0.2906 | -0.0473 | 0.2906 | | No log | 2.2353 | 38 | 0.2973 | 0.0 | 0.2973 | | No log | 2.3529 | 40 | 0.3635 | 0.0 | 0.3635 | | No log | 2.4706 | 42 | 0.4742 | -0.0268 | 0.4742 | | No log | 2.5882 | 44 | 0.4561 | -0.0185 | 0.4561 | | No log | 2.7059 | 46 | 0.3327 | 0.0 | 0.3327 | | No log | 2.8235 | 48 | 0.2840 | 0.0 | 0.2840 | | No log | 2.9412 | 50 | 0.2878 | -0.0235 | 0.2878 | | No log | 3.0588 | 52 | 0.2902 | -0.0235 | 0.2902 | | No log | 3.1765 | 54 | 0.2821 | -0.0473 | 0.2821 | | No log | 3.2941 | 56 | 0.2813 | 0.0 | 0.2813 | | No log | 3.4118 | 58 | 0.3125 | 0.0 | 0.3125 | | No log | 3.5294 | 60 | 0.3580 | 0.0 | 0.3580 | | No log | 3.6471 | 62 | 0.3412 | 0.0 | 0.3412 | | No log | 3.7647 | 64 | 0.3136 | 0.0 | 0.3136 | | No log | 3.8824 | 66 | 0.2971 | -0.0235 | 0.2971 | | No log | 4.0 | 68 | 0.2918 | -0.0135 | 0.2918 | | No log | 4.1176 | 70 | 0.2894 | -0.0235 | 0.2894 | | No log | 4.2353 | 72 | 0.2973 | 0.0 | 0.2973 | | No log | 4.3529 | 74 | 0.3060 | 0.0 | 0.3060 | | No log | 4.4706 | 76 | 0.3066 | 0.0 | 0.3066 | | No log | 4.5882 | 78 | 0.3086 | 0.0 | 0.3086 | | No log | 4.7059 | 80 | 0.3207 | 0.0 | 0.3207 | | No log | 4.8235 | 82 | 0.3228 | 0.0 | 0.3228 | | No log | 4.9412 | 84 | 0.3232 | 0.0 | 0.3232 | | No log | 5.0588 | 86 | 0.3306 | 0.0 | 0.3306 | | No log | 5.1765 | 88 | 0.3322 | 0.0 | 0.3322 | | No log | 5.2941 | 90 | 0.3595 | 0.0 | 0.3595 | | No log | 5.4118 | 92 | 0.3659 | 0.0 | 0.3659 | | No log | 5.5294 | 94 | 0.3968 | 0.0 | 0.3968 | | No log | 5.6471 | 96 | 0.4325 | -0.0185 | 0.4325 | | No log | 5.7647 | 98 | 0.4240 | -0.0185 | 0.4240 | | No log | 5.8824 | 100 | 0.3886 | -0.0096 | 0.3886 | | No log | 6.0 | 102 | 0.3688 | -0.0096 | 0.3688 | | No log | 6.1176 | 104 | 0.3669 | -0.0096 | 0.3669 | | No log | 6.2353 | 106 | 0.3824 | -0.0096 | 0.3824 | | No log | 6.3529 | 108 | 0.3765 | -0.0323 | 0.3765 | | No log | 6.4706 | 110 | 0.3534 | -0.0235 | 0.3534 | | No log | 6.5882 | 112 | 0.3724 | -0.0235 | 0.3724 | | No log | 6.7059 | 114 | 0.4165 | -0.0323 | 0.4165 | | No log | 6.8235 | 116 | 0.4596 | -0.0533 | 0.4596 | | No log | 6.9412 | 118 | 0.4708 | -0.0591 | 0.4708 | | No log | 7.0588 | 120 | 0.4502 | -0.0405 | 0.4502 | | No log | 7.1765 | 122 | 0.4102 | -0.0323 | 0.4102 | | No log | 7.2941 | 124 | 0.4035 | -0.0323 | 0.4035 | | No log | 7.4118 | 126 | 0.4253 | -0.0323 | 0.4253 | | No log | 7.5294 | 128 | 0.4225 | -0.0323 | 0.4225 | | No log | 7.6471 | 130 | 0.4086 | -0.0323 | 0.4086 | | No log | 7.7647 | 132 | 0.4280 | -0.0260 | 0.4280 | | No log | 7.8824 | 134 | 0.4752 | -0.0233 | 0.4752 | | No log | 8.0 | 136 | 0.4963 | -0.0193 | 0.4963 | | No log | 8.1176 | 138 | 0.5295 | -0.0104 | 0.5295 | | No log | 8.2353 | 140 | 0.5401 | -0.0104 | 0.5401 | | No log | 8.3529 | 142 | 0.5096 | -0.0193 | 0.5096 | | No log | 8.4706 | 144 | 0.4677 | -0.0279 | 0.4677 | | No log | 8.5882 | 146 | 0.4416 | -0.0135 | 0.4416 | | No log | 8.7059 | 148 | 0.4452 | -0.0135 | 0.4452 | | No log | 8.8235 | 150 | 0.4725 | -0.0279 | 0.4725 | | No log | 8.9412 | 152 | 0.4991 | -0.0233 | 0.4991 | | No log | 9.0588 | 154 | 0.5151 | -0.0251 | 0.5151 | | No log | 9.1765 | 156 | 0.5160 | -0.0251 | 0.5160 | | No log | 9.2941 | 158 | 0.5242 | -0.0251 | 0.5242 | | No log | 9.4118 | 160 | 0.5189 | -0.0251 | 0.5189 | | No log | 9.5294 | 162 | 0.5080 | -0.0193 | 0.5080 | | No log | 9.6471 | 164 | 0.4972 | -0.0233 | 0.4972 | | No log | 9.7647 | 166 | 0.4929 | -0.0167 | 0.4929 | | No log | 9.8824 | 168 | 0.4916 | -0.0345 | 0.4916 | | No log | 10.0 | 170 | 0.4917 | -0.0345 | 0.4917 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1