--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: Arabic_FineTuningAraBERT_AugV4-trial2_k1_task1_organization_fold0 results: [] --- # Arabic_FineTuningAraBERT_AugV4-trial2_k1_task1_organization_fold0 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: 0.8043 - Qwk: 0.7268 - Mse: 0.8043 - Rmse: 0.8968 ## 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: 8 - eval_batch_size: 8 - 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 | Rmse | |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:| | No log | 0.0667 | 2 | 5.3857 | 0.0 | 5.3857 | 2.3207 | | No log | 0.1333 | 4 | 3.2299 | 0.0027 | 3.2299 | 1.7972 | | No log | 0.2 | 6 | 1.7033 | 0.1778 | 1.7033 | 1.3051 | | No log | 0.2667 | 8 | 1.2584 | 0.2159 | 1.2584 | 1.1218 | | No log | 0.3333 | 10 | 1.2060 | 0.0742 | 1.2060 | 1.0982 | | No log | 0.4 | 12 | 1.3288 | 0.4854 | 1.3288 | 1.1528 | | No log | 0.4667 | 14 | 1.4327 | 0.3259 | 1.4327 | 1.1970 | | No log | 0.5333 | 16 | 1.5300 | 0.2184 | 1.5300 | 1.2369 | | No log | 0.6 | 18 | 1.5359 | 0.2435 | 1.5359 | 1.2393 | | No log | 0.6667 | 20 | 1.3307 | 0.3226 | 1.3307 | 1.1536 | | No log | 0.7333 | 22 | 1.1492 | 0.4830 | 1.1492 | 1.0720 | | No log | 0.8 | 24 | 0.8873 | 0.5106 | 0.8873 | 0.9420 | | No log | 0.8667 | 26 | 0.9113 | 0.3364 | 0.9113 | 0.9546 | | No log | 0.9333 | 28 | 0.8242 | 0.5323 | 0.8242 | 0.9078 | | No log | 1.0 | 30 | 1.1596 | 0.3831 | 1.1596 | 1.0768 | | No log | 1.0667 | 32 | 1.3726 | 0.3816 | 1.3726 | 1.1716 | | No log | 1.1333 | 34 | 1.4508 | 0.3226 | 1.4508 | 1.2045 | | No log | 1.2 | 36 | 1.4111 | 0.3816 | 1.4111 | 1.1879 | | No log | 1.2667 | 38 | 1.1806 | 0.3831 | 1.1806 | 1.0865 | | No log | 1.3333 | 40 | 0.9499 | 0.5312 | 0.9499 | 0.9746 | | No log | 1.4 | 42 | 0.8107 | 0.5304 | 0.8107 | 0.9004 | | No log | 1.4667 | 44 | 0.6970 | 0.6075 | 0.6970 | 0.8348 | | No log | 1.5333 | 46 | 0.7168 | 0.5674 | 0.7168 | 0.8467 | | No log | 1.6 | 48 | 0.7132 | 0.5674 | 0.7132 | 0.8445 | | No log | 1.6667 | 50 | 0.7372 | 0.5674 | 0.7372 | 0.8586 | | No log | 1.7333 | 52 | 0.6976 | 0.5263 | 0.6976 | 0.8352 | | No log | 1.8 | 54 | 0.7046 | 0.5413 | 0.7046 | 0.8394 | | No log | 1.8667 | 56 | 0.7251 | 0.5545 | 0.7251 | 0.8515 | | No log | 1.9333 | 58 | 0.7257 | 0.5811 | 0.7257 | 0.8519 | | No log | 2.0 | 60 | 0.8599 | 0.7042 | 0.8599 | 0.9273 | | No log | 2.0667 | 62 | 1.0463 | 0.5742 | 1.0463 | 1.0229 | | No log | 2.1333 | 64 | 0.9787 | 0.6564 | 0.9787 | 0.9893 | | No log | 2.2 | 66 | 0.8863 | 0.6503 | 0.8863 | 0.9414 | | No log | 2.2667 | 68 | 0.8468 | 0.7123 | 0.8468 | 0.9202 | | No log | 2.3333 | 70 | 0.7648 | 0.5723 | 0.7648 | 0.8745 | | No log | 2.4 | 72 | 0.6991 | 0.5633 | 0.6991 | 0.8361 | | No log | 2.4667 | 74 | 0.7304 | 0.5633 | 0.7304 | 0.8546 | | No log | 2.5333 | 76 | 0.9507 | 0.7525 | 0.9507 | 0.9751 | | No log | 2.6 | 78 | 1.1681 | 0.7221 | 1.1681 | 1.0808 | | No log | 2.6667 | 80 | 1.1511 | 0.6127 | 1.1511 | 1.0729 | | No log | 2.7333 | 82 | 0.9790 | 0.6776 | 0.9790 | 0.9894 | | No log | 2.8 | 84 | 0.6980 | 0.7008 | 0.6980 | 0.8355 | | No log | 2.8667 | 86 | 0.5887 | 0.6165 | 0.5887 | 0.7673 | | No log | 2.9333 | 88 | 0.6506 | 0.6355 | 0.6506 | 0.8066 | | No log | 3.0 | 90 | 0.5959 | 0.6355 | 0.5959 | 0.7719 | | No log | 3.0667 | 92 | 0.5404 | 0.6719 | 0.5404 | 0.7351 | | No log | 3.1333 | 94 | 0.7248 | 0.7986 | 0.7248 | 0.8514 | | No log | 3.2 | 96 | 1.0280 | 0.6776 | 1.0280 | 1.0139 | | No log | 3.2667 | 98 | 1.2998 | 0.6119 | 1.2998 | 1.1401 | | No log | 3.3333 | 100 | 1.2866 | 0.6119 | 1.2866 | 1.1343 | | No log | 3.4 | 102 | 1.0527 | 0.6550 | 1.0527 | 1.0260 | | No log | 3.4667 | 104 | 0.7864 | 0.7627 | 0.7864 | 0.8868 | | No log | 3.5333 | 106 | 0.6154 | 0.7439 | 0.6154 | 0.7845 | | No log | 3.6 | 108 | 0.5424 | 0.7618 | 0.5424 | 0.7365 | | No log | 3.6667 | 110 | 0.5244 | 0.7533 | 0.5244 | 0.7241 | | No log | 3.7333 | 112 | 0.5468 | 0.7533 | 0.5468 | 0.7395 | | No log | 3.8 | 114 | 0.6163 | 0.7355 | 0.6163 | 0.7851 | | No log | 3.8667 | 116 | 0.6544 | 0.7439 | 0.6544 | 0.8089 | | No log | 3.9333 | 118 | 0.6669 | 0.7439 | 0.6669 | 0.8166 | | No log | 4.0 | 120 | 0.6427 | 0.7367 | 0.6427 | 0.8017 | | No log | 4.0667 | 122 | 0.7210 | 0.7704 | 0.7210 | 0.8491 | | No log | 4.1333 | 124 | 0.7779 | 0.7986 | 0.7779 | 0.8820 | | No log | 4.2 | 126 | 0.7765 | 0.8168 | 0.7765 | 0.8812 | | No log | 4.2667 | 128 | 0.7463 | 0.8168 | 0.7463 | 0.8639 | | No log | 4.3333 | 130 | 0.6790 | 0.7439 | 0.6790 | 0.8240 | | No log | 4.4 | 132 | 0.6092 | 0.7204 | 0.6092 | 0.7805 | | No log | 4.4667 | 134 | 0.6065 | 0.7181 | 0.6065 | 0.7788 | | No log | 4.5333 | 136 | 0.6599 | 0.7439 | 0.6599 | 0.8123 | | No log | 4.6 | 138 | 0.7979 | 0.8098 | 0.7979 | 0.8933 | | No log | 4.6667 | 140 | 0.8938 | 0.8098 | 0.8938 | 0.9454 | | No log | 4.7333 | 142 | 0.8511 | 0.8098 | 0.8511 | 0.9225 | | No log | 4.8 | 144 | 0.7067 | 0.7529 | 0.7067 | 0.8407 | | No log | 4.8667 | 146 | 0.5945 | 0.7355 | 0.5945 | 0.7711 | | No log | 4.9333 | 148 | 0.5649 | 0.7008 | 0.5649 | 0.7516 | | No log | 5.0 | 150 | 0.5981 | 0.7355 | 0.5981 | 0.7733 | | No log | 5.0667 | 152 | 0.6656 | 0.7529 | 0.6656 | 0.8159 | | No log | 5.1333 | 154 | 0.7173 | 0.7529 | 0.7173 | 0.8469 | | No log | 5.2 | 156 | 0.7542 | 0.7801 | 0.7542 | 0.8684 | | No log | 5.2667 | 158 | 0.7518 | 0.7801 | 0.7518 | 0.8671 | | No log | 5.3333 | 160 | 0.8161 | 0.7346 | 0.8161 | 0.9034 | | No log | 5.4 | 162 | 0.8351 | 0.7779 | 0.8351 | 0.9139 | | No log | 5.4667 | 164 | 0.7792 | 0.7779 | 0.7792 | 0.8827 | | No log | 5.5333 | 166 | 0.7254 | 0.7196 | 0.7254 | 0.8517 | | No log | 5.6 | 168 | 0.6935 | 0.7382 | 0.6935 | 0.8328 | | No log | 5.6667 | 170 | 0.6844 | 0.7599 | 0.6844 | 0.8273 | | No log | 5.7333 | 172 | 0.7231 | 0.7689 | 0.7231 | 0.8503 | | No log | 5.8 | 174 | 0.7996 | 0.7525 | 0.7996 | 0.8942 | | No log | 5.8667 | 176 | 0.8551 | 0.7616 | 0.8551 | 0.9247 | | No log | 5.9333 | 178 | 0.8262 | 0.7616 | 0.8262 | 0.9090 | | No log | 6.0 | 180 | 0.7452 | 0.8098 | 0.7452 | 0.8633 | | No log | 6.0667 | 182 | 0.6525 | 0.7529 | 0.6525 | 0.8078 | | No log | 6.1333 | 184 | 0.6447 | 0.7529 | 0.6447 | 0.8029 | | No log | 6.2 | 186 | 0.6647 | 0.7529 | 0.6647 | 0.8153 | | No log | 6.2667 | 188 | 0.7182 | 0.7529 | 0.7182 | 0.8474 | | No log | 6.3333 | 190 | 0.8144 | 0.7937 | 0.8144 | 0.9024 | | No log | 6.4 | 192 | 0.8856 | 0.7937 | 0.8856 | 0.9411 | | No log | 6.4667 | 194 | 0.9341 | 0.7937 | 0.9341 | 0.9665 | | No log | 6.5333 | 196 | 0.9351 | 0.7612 | 0.9351 | 0.9670 | | No log | 6.6 | 198 | 0.8674 | 0.7979 | 0.8674 | 0.9313 | | No log | 6.6667 | 200 | 0.8485 | 0.7979 | 0.8485 | 0.9211 | | No log | 6.7333 | 202 | 0.8596 | 0.7979 | 0.8596 | 0.9272 | | No log | 6.8 | 204 | 0.8493 | 0.7979 | 0.8493 | 0.9216 | | No log | 6.8667 | 206 | 0.8583 | 0.7979 | 0.8583 | 0.9265 | | No log | 6.9333 | 208 | 0.8988 | 0.7979 | 0.8988 | 0.9481 | | No log | 7.0 | 210 | 0.8918 | 0.7979 | 0.8918 | 0.9444 | | No log | 7.0667 | 212 | 0.8785 | 0.7430 | 0.8785 | 0.9373 | | No log | 7.1333 | 214 | 0.8492 | 0.7144 | 0.8492 | 0.9215 | | No log | 7.2 | 216 | 0.7861 | 0.7144 | 0.7861 | 0.8866 | | No log | 7.2667 | 218 | 0.7437 | 0.6997 | 0.7437 | 0.8624 | | No log | 7.3333 | 220 | 0.7548 | 0.6997 | 0.7548 | 0.8688 | | No log | 7.4 | 222 | 0.7754 | 0.7268 | 0.7754 | 0.8806 | | No log | 7.4667 | 224 | 0.7531 | 0.7268 | 0.7531 | 0.8678 | | No log | 7.5333 | 226 | 0.7676 | 0.7268 | 0.7676 | 0.8761 | | No log | 7.6 | 228 | 0.8205 | 0.7268 | 0.8205 | 0.9058 | | No log | 7.6667 | 230 | 0.8726 | 0.7346 | 0.8726 | 0.9341 | | No log | 7.7333 | 232 | 0.8584 | 0.7346 | 0.8584 | 0.9265 | | No log | 7.8 | 234 | 0.8172 | 0.7346 | 0.8172 | 0.9040 | | No log | 7.8667 | 236 | 0.8080 | 0.7268 | 0.8080 | 0.8989 | | No log | 7.9333 | 238 | 0.8049 | 0.7268 | 0.8049 | 0.8972 | | No log | 8.0 | 240 | 0.8290 | 0.7268 | 0.8290 | 0.9105 | | No log | 8.0667 | 242 | 0.8446 | 0.7268 | 0.8446 | 0.9190 | | No log | 8.1333 | 244 | 0.8433 | 0.7268 | 0.8433 | 0.9183 | | No log | 8.2 | 246 | 0.8181 | 0.7268 | 0.8181 | 0.9045 | | No log | 8.2667 | 248 | 0.8030 | 0.7268 | 0.8030 | 0.8961 | | No log | 8.3333 | 250 | 0.7975 | 0.7268 | 0.7975 | 0.8930 | | No log | 8.4 | 252 | 0.8155 | 0.6997 | 0.8155 | 0.9030 | | No log | 8.4667 | 254 | 0.8388 | 0.7068 | 0.8388 | 0.9159 | | No log | 8.5333 | 256 | 0.8509 | 0.7068 | 0.8509 | 0.9225 | | No log | 8.6 | 258 | 0.8361 | 0.7068 | 0.8361 | 0.9144 | | No log | 8.6667 | 260 | 0.8024 | 0.6997 | 0.8024 | 0.8958 | | No log | 8.7333 | 262 | 0.7665 | 0.6997 | 0.7665 | 0.8755 | | No log | 8.8 | 264 | 0.7415 | 0.6932 | 0.7415 | 0.8611 | | No log | 8.8667 | 266 | 0.7288 | 0.6932 | 0.7288 | 0.8537 | | No log | 8.9333 | 268 | 0.7342 | 0.6932 | 0.7342 | 0.8568 | | No log | 9.0 | 270 | 0.7290 | 0.6932 | 0.7290 | 0.8538 | | No log | 9.0667 | 272 | 0.7358 | 0.6932 | 0.7358 | 0.8578 | | No log | 9.1333 | 274 | 0.7405 | 0.7196 | 0.7405 | 0.8605 | | No log | 9.2 | 276 | 0.7587 | 0.7196 | 0.7587 | 0.8711 | | No log | 9.2667 | 278 | 0.7844 | 0.7196 | 0.7844 | 0.8856 | | No log | 9.3333 | 280 | 0.8017 | 0.7268 | 0.8017 | 0.8954 | | No log | 9.4 | 282 | 0.8107 | 0.7268 | 0.8107 | 0.9004 | | No log | 9.4667 | 284 | 0.8114 | 0.7268 | 0.8114 | 0.9008 | | No log | 9.5333 | 286 | 0.8111 | 0.7268 | 0.8111 | 0.9006 | | No log | 9.6 | 288 | 0.8117 | 0.7268 | 0.8117 | 0.9009 | | No log | 9.6667 | 290 | 0.8142 | 0.7346 | 0.8142 | 0.9023 | | No log | 9.7333 | 292 | 0.8104 | 0.7268 | 0.8104 | 0.9002 | | No log | 9.8 | 294 | 0.8107 | 0.7268 | 0.8107 | 0.9004 | | No log | 9.8667 | 296 | 0.8083 | 0.7268 | 0.8083 | 0.8991 | | No log | 9.9333 | 298 | 0.8059 | 0.7268 | 0.8059 | 0.8977 | | No log | 10.0 | 300 | 0.8043 | 0.7268 | 0.8043 | 0.8968 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1