--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_development_task1_fold1 results: [] --- # arabert_cross_development_task1_fold1 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: 0.7152 - Qwk: 0.1109 - Mse: 0.7153 ## 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 | 5.0133 | -0.0040 | 5.0069 | | No log | 0.25 | 4 | 1.7271 | 0.0220 | 1.7233 | | No log | 0.375 | 6 | 0.6069 | 0.0575 | 0.6049 | | No log | 0.5 | 8 | 0.6108 | 0.0838 | 0.6102 | | No log | 0.625 | 10 | 0.6811 | -0.0132 | 0.6805 | | No log | 0.75 | 12 | 0.6094 | 0.1119 | 0.6084 | | No log | 0.875 | 14 | 0.6389 | 0.0138 | 0.6386 | | No log | 1.0 | 16 | 0.6607 | -0.0302 | 0.6606 | | No log | 1.125 | 18 | 0.8561 | 0.0 | 0.8561 | | No log | 1.25 | 20 | 0.8772 | 0.0192 | 0.8774 | | No log | 1.375 | 22 | 0.6488 | 0.1233 | 0.6484 | | No log | 1.5 | 24 | 0.6095 | 0.0553 | 0.6090 | | No log | 1.625 | 26 | 0.8548 | 0.0249 | 0.8549 | | No log | 1.75 | 28 | 0.8236 | 0.0 | 0.8237 | | No log | 1.875 | 30 | 0.6385 | 0.0263 | 0.6382 | | No log | 2.0 | 32 | 0.6856 | -0.0056 | 0.6854 | | No log | 2.125 | 34 | 0.7166 | 0.0 | 0.7165 | | No log | 2.25 | 36 | 0.6505 | 0.0135 | 0.6503 | | No log | 2.375 | 38 | 0.6867 | 0.0 | 0.6865 | | No log | 2.5 | 40 | 0.7602 | 0.0 | 0.7602 | | No log | 2.625 | 42 | 0.7896 | 0.0 | 0.7897 | | No log | 2.75 | 44 | 0.8485 | 0.0 | 0.8487 | | No log | 2.875 | 46 | 0.8089 | 0.0 | 0.8090 | | No log | 3.0 | 48 | 0.8838 | 0.0 | 0.8841 | | No log | 3.125 | 50 | 1.0443 | 0.0 | 1.0448 | | No log | 3.25 | 52 | 1.2312 | 0.0 | 1.2319 | | No log | 3.375 | 54 | 1.2836 | 0.0 | 1.2843 | | No log | 3.5 | 56 | 1.0837 | 0.0 | 1.0842 | | No log | 3.625 | 58 | 0.9529 | 0.0 | 0.9532 | | No log | 3.75 | 60 | 0.9030 | 0.0 | 0.9032 | | No log | 3.875 | 62 | 0.9117 | 0.0 | 0.9119 | | No log | 4.0 | 64 | 0.8372 | 0.0 | 0.8373 | | No log | 4.125 | 66 | 0.8288 | 0.0 | 0.8289 | | No log | 4.25 | 68 | 0.7667 | 0.0 | 0.7667 | | No log | 4.375 | 70 | 0.8226 | 0.0 | 0.8228 | | No log | 4.5 | 72 | 0.9046 | 0.0 | 0.9050 | | No log | 4.625 | 74 | 1.1055 | 0.0 | 1.1061 | | No log | 4.75 | 76 | 1.1209 | 0.0 | 1.1216 | | No log | 4.875 | 78 | 0.9195 | 0.0 | 0.9199 | | No log | 5.0 | 80 | 0.7954 | 0.0554 | 0.7956 | | No log | 5.125 | 82 | 0.8199 | 0.0 | 0.8203 | | No log | 5.25 | 84 | 0.6997 | 0.1731 | 0.6999 | | No log | 5.375 | 86 | 0.6765 | 0.1731 | 0.6766 | | No log | 5.5 | 88 | 0.8095 | 0.0554 | 0.8099 | | No log | 5.625 | 90 | 0.7989 | 0.0554 | 0.7992 | | No log | 5.75 | 92 | 0.7088 | 0.1731 | 0.7089 | | No log | 5.875 | 94 | 0.8201 | 0.0554 | 0.8205 | | No log | 6.0 | 96 | 1.0195 | 0.0 | 1.0201 | | No log | 6.125 | 98 | 1.0328 | 0.0 | 1.0335 | | No log | 6.25 | 100 | 0.9344 | 0.0 | 0.9349 | | No log | 6.375 | 102 | 0.7485 | 0.0906 | 0.7487 | | No log | 6.5 | 104 | 0.6810 | 0.1387 | 0.6811 | | No log | 6.625 | 106 | 0.7638 | 0.0672 | 0.7640 | | No log | 6.75 | 108 | 0.9339 | 0.0 | 0.9342 | | No log | 6.875 | 110 | 0.9824 | 0.0 | 0.9828 | | No log | 7.0 | 112 | 0.9198 | 0.0 | 0.9202 | | No log | 7.125 | 114 | 0.8078 | 0.0554 | 0.8080 | | No log | 7.25 | 116 | 0.6480 | 0.1412 | 0.6480 | | No log | 7.375 | 118 | 0.6108 | 0.1780 | 0.6107 | | No log | 7.5 | 120 | 0.6581 | 0.1109 | 0.6581 | | No log | 7.625 | 122 | 0.7813 | 0.0554 | 0.7815 | | No log | 7.75 | 124 | 0.8870 | 0.0 | 0.8873 | | No log | 7.875 | 126 | 0.9244 | 0.0 | 0.9247 | | No log | 8.0 | 128 | 0.9045 | 0.0554 | 0.9048 | | No log | 8.125 | 130 | 0.8522 | 0.0554 | 0.8524 | | No log | 8.25 | 132 | 0.8434 | 0.0554 | 0.8436 | | No log | 8.375 | 134 | 0.8530 | 0.0554 | 0.8532 | | No log | 8.5 | 136 | 0.8770 | 0.0554 | 0.8772 | | No log | 8.625 | 138 | 0.8451 | 0.0554 | 0.8453 | | No log | 8.75 | 140 | 0.8325 | 0.0554 | 0.8327 | | No log | 8.875 | 142 | 0.8378 | 0.0554 | 0.8380 | | No log | 9.0 | 144 | 0.8214 | 0.0554 | 0.8216 | | No log | 9.125 | 146 | 0.7888 | 0.0554 | 0.7890 | | No log | 9.25 | 148 | 0.7536 | 0.0376 | 0.7537 | | No log | 9.375 | 150 | 0.7389 | 0.0612 | 0.7390 | | No log | 9.5 | 152 | 0.7209 | 0.0844 | 0.7210 | | No log | 9.625 | 154 | 0.7172 | 0.1232 | 0.7173 | | No log | 9.75 | 156 | 0.7125 | 0.1109 | 0.7126 | | No log | 9.875 | 158 | 0.7149 | 0.1109 | 0.7150 | | No log | 10.0 | 160 | 0.7152 | 0.1109 | 0.7153 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1