ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k20_task1_organization
This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6928
- Qwk: 0.6096
- Mse: 0.6928
- Rmse: 0.8323
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: 100
Training results
Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
---|---|---|---|---|---|---|
No log | 0.0204 | 2 | 5.2781 | -0.0163 | 5.2781 | 2.2974 |
No log | 0.0408 | 4 | 3.4104 | 0.0445 | 3.4105 | 1.8467 |
No log | 0.0612 | 6 | 2.5206 | -0.0928 | 2.5206 | 1.5876 |
No log | 0.0816 | 8 | 1.6544 | 0.1402 | 1.6544 | 1.2862 |
No log | 0.1020 | 10 | 1.2417 | 0.2185 | 1.2417 | 1.1143 |
No log | 0.1224 | 12 | 1.0991 | 0.3305 | 1.0991 | 1.0484 |
No log | 0.1429 | 14 | 1.0545 | 0.3433 | 1.0545 | 1.0269 |
No log | 0.1633 | 16 | 1.1757 | 0.2565 | 1.1757 | 1.0843 |
No log | 0.1837 | 18 | 1.2550 | 0.2754 | 1.2550 | 1.1203 |
No log | 0.2041 | 20 | 1.0493 | 0.3162 | 1.0493 | 1.0244 |
No log | 0.2245 | 22 | 1.0488 | 0.4038 | 1.0488 | 1.0241 |
No log | 0.2449 | 24 | 1.0843 | 0.4275 | 1.0843 | 1.0413 |
No log | 0.2653 | 26 | 1.3000 | 0.2825 | 1.3000 | 1.1402 |
No log | 0.2857 | 28 | 1.8720 | 0.0358 | 1.8720 | 1.3682 |
No log | 0.3061 | 30 | 2.3271 | -0.1650 | 2.3271 | 1.5255 |
No log | 0.3265 | 32 | 1.4564 | 0.1839 | 1.4564 | 1.2068 |
No log | 0.3469 | 34 | 1.0335 | 0.4195 | 1.0335 | 1.0166 |
No log | 0.3673 | 36 | 0.9945 | 0.3436 | 0.9945 | 0.9972 |
No log | 0.3878 | 38 | 1.0714 | 0.4022 | 1.0714 | 1.0351 |
No log | 0.4082 | 40 | 1.3934 | 0.2724 | 1.3934 | 1.1804 |
No log | 0.4286 | 42 | 1.4627 | 0.2273 | 1.4627 | 1.2094 |
No log | 0.4490 | 44 | 1.1573 | 0.3789 | 1.1573 | 1.0758 |
No log | 0.4694 | 46 | 0.9842 | 0.5318 | 0.9842 | 0.9921 |
No log | 0.4898 | 48 | 0.9717 | 0.5080 | 0.9717 | 0.9858 |
No log | 0.5102 | 50 | 0.9445 | 0.4971 | 0.9445 | 0.9719 |
No log | 0.5306 | 52 | 1.0291 | 0.3873 | 1.0291 | 1.0144 |
No log | 0.5510 | 54 | 1.0098 | 0.3961 | 1.0098 | 1.0049 |
No log | 0.5714 | 56 | 0.9101 | 0.4395 | 0.9101 | 0.9540 |
No log | 0.5918 | 58 | 0.9313 | 0.4202 | 0.9313 | 0.9650 |
No log | 0.6122 | 60 | 0.9259 | 0.4348 | 0.9259 | 0.9622 |
No log | 0.6327 | 62 | 1.0292 | 0.4632 | 1.0292 | 1.0145 |
No log | 0.6531 | 64 | 1.2215 | 0.3031 | 1.2215 | 1.1052 |
No log | 0.6735 | 66 | 1.0492 | 0.4567 | 1.0492 | 1.0243 |
No log | 0.6939 | 68 | 0.8616 | 0.5526 | 0.8616 | 0.9282 |
No log | 0.7143 | 70 | 1.0007 | 0.4778 | 1.0007 | 1.0004 |
No log | 0.7347 | 72 | 1.2435 | 0.4152 | 1.2435 | 1.1151 |
No log | 0.7551 | 74 | 1.0029 | 0.4329 | 1.0029 | 1.0014 |
No log | 0.7755 | 76 | 0.9524 | 0.5251 | 0.9524 | 0.9759 |
No log | 0.7959 | 78 | 1.0880 | 0.4195 | 1.0880 | 1.0431 |
No log | 0.8163 | 80 | 1.0978 | 0.4253 | 1.0978 | 1.0477 |
No log | 0.8367 | 82 | 0.9895 | 0.4954 | 0.9895 | 0.9947 |
No log | 0.8571 | 84 | 0.9191 | 0.5160 | 0.9191 | 0.9587 |
No log | 0.8776 | 86 | 0.9214 | 0.4675 | 0.9214 | 0.9599 |
No log | 0.8980 | 88 | 0.9076 | 0.4858 | 0.9076 | 0.9527 |
No log | 0.9184 | 90 | 0.8456 | 0.5362 | 0.8456 | 0.9196 |
No log | 0.9388 | 92 | 0.9760 | 0.4030 | 0.9760 | 0.9879 |
No log | 0.9592 | 94 | 1.6512 | -0.0084 | 1.6512 | 1.2850 |
No log | 0.9796 | 96 | 1.5812 | 0.0308 | 1.5812 | 1.2575 |
No log | 1.0 | 98 | 1.1015 | 0.2517 | 1.1015 | 1.0495 |
No log | 1.0204 | 100 | 0.8865 | 0.5362 | 0.8865 | 0.9415 |
No log | 1.0408 | 102 | 0.8416 | 0.5991 | 0.8416 | 0.9174 |
No log | 1.0612 | 104 | 0.8374 | 0.5886 | 0.8374 | 0.9151 |
No log | 1.0816 | 106 | 0.7919 | 0.5779 | 0.7919 | 0.8899 |
No log | 1.1020 | 108 | 0.7860 | 0.5813 | 0.7860 | 0.8866 |
No log | 1.1224 | 110 | 0.7995 | 0.6331 | 0.7995 | 0.8942 |
No log | 1.1429 | 112 | 0.7655 | 0.6496 | 0.7655 | 0.8749 |
No log | 1.1633 | 114 | 0.7541 | 0.6514 | 0.7541 | 0.8684 |
No log | 1.1837 | 116 | 0.7695 | 0.6221 | 0.7695 | 0.8772 |
No log | 1.2041 | 118 | 0.7697 | 0.6135 | 0.7697 | 0.8773 |
No log | 1.2245 | 120 | 0.7710 | 0.5913 | 0.7710 | 0.8781 |
No log | 1.2449 | 122 | 0.7616 | 0.6189 | 0.7616 | 0.8727 |
No log | 1.2653 | 124 | 0.8054 | 0.6166 | 0.8054 | 0.8974 |
No log | 1.2857 | 126 | 0.9775 | 0.5258 | 0.9775 | 0.9887 |
No log | 1.3061 | 128 | 1.0841 | 0.5098 | 1.0841 | 1.0412 |
No log | 1.3265 | 130 | 1.0496 | 0.5324 | 1.0496 | 1.0245 |
No log | 1.3469 | 132 | 0.9969 | 0.5546 | 0.9969 | 0.9985 |
No log | 1.3673 | 134 | 0.8705 | 0.6105 | 0.8705 | 0.9330 |
No log | 1.3878 | 136 | 0.8166 | 0.6778 | 0.8166 | 0.9037 |
No log | 1.4082 | 138 | 0.8283 | 0.6653 | 0.8283 | 0.9101 |
No log | 1.4286 | 140 | 0.8765 | 0.6228 | 0.8765 | 0.9362 |
No log | 1.4490 | 142 | 0.8835 | 0.6261 | 0.8835 | 0.9400 |
No log | 1.4694 | 144 | 0.8836 | 0.6238 | 0.8836 | 0.9400 |
No log | 1.4898 | 146 | 1.0274 | 0.5694 | 1.0274 | 1.0136 |
No log | 1.5102 | 148 | 1.0584 | 0.5429 | 1.0584 | 1.0288 |
No log | 1.5306 | 150 | 0.9162 | 0.6090 | 0.9162 | 0.9572 |
No log | 1.5510 | 152 | 0.7901 | 0.6728 | 0.7901 | 0.8889 |
No log | 1.5714 | 154 | 0.8000 | 0.6577 | 0.8000 | 0.8945 |
No log | 1.5918 | 156 | 0.8592 | 0.6781 | 0.8592 | 0.9269 |
No log | 1.6122 | 158 | 0.9939 | 0.5917 | 0.9939 | 0.9969 |
No log | 1.6327 | 160 | 0.9930 | 0.5795 | 0.9930 | 0.9965 |
No log | 1.6531 | 162 | 0.8973 | 0.6402 | 0.8973 | 0.9472 |
No log | 1.6735 | 164 | 0.8011 | 0.6480 | 0.8011 | 0.8950 |
No log | 1.6939 | 166 | 0.8234 | 0.6813 | 0.8234 | 0.9074 |
No log | 1.7143 | 168 | 0.9876 | 0.6007 | 0.9876 | 0.9938 |
No log | 1.7347 | 170 | 1.1225 | 0.5134 | 1.1225 | 1.0595 |
No log | 1.7551 | 172 | 1.0429 | 0.5393 | 1.0429 | 1.0212 |
No log | 1.7755 | 174 | 0.9508 | 0.6464 | 0.9508 | 0.9751 |
No log | 1.7959 | 176 | 0.9113 | 0.6598 | 0.9113 | 0.9546 |
No log | 1.8163 | 178 | 0.9206 | 0.6204 | 0.9206 | 0.9595 |
No log | 1.8367 | 180 | 0.9775 | 0.5618 | 0.9775 | 0.9887 |
No log | 1.8571 | 182 | 0.9167 | 0.5794 | 0.9167 | 0.9574 |
No log | 1.8776 | 184 | 0.8218 | 0.5619 | 0.8218 | 0.9065 |
No log | 1.8980 | 186 | 0.8256 | 0.5195 | 0.8256 | 0.9086 |
No log | 1.9184 | 188 | 0.8296 | 0.5830 | 0.8296 | 0.9108 |
No log | 1.9388 | 190 | 0.9826 | 0.5358 | 0.9826 | 0.9913 |
No log | 1.9592 | 192 | 1.1710 | 0.4653 | 1.1710 | 1.0821 |
No log | 1.9796 | 194 | 1.1736 | 0.4644 | 1.1736 | 1.0833 |
No log | 2.0 | 196 | 1.1128 | 0.4786 | 1.1128 | 1.0549 |
No log | 2.0204 | 198 | 0.9607 | 0.5599 | 0.9607 | 0.9802 |
No log | 2.0408 | 200 | 0.9190 | 0.5570 | 0.9190 | 0.9587 |
No log | 2.0612 | 202 | 0.9199 | 0.5599 | 0.9199 | 0.9591 |
No log | 2.0816 | 204 | 0.9813 | 0.5483 | 0.9813 | 0.9906 |
No log | 2.1020 | 206 | 1.0288 | 0.5121 | 1.0288 | 1.0143 |
No log | 2.1224 | 208 | 1.0146 | 0.5280 | 1.0146 | 1.0073 |
No log | 2.1429 | 210 | 0.9023 | 0.6169 | 0.9023 | 0.9499 |
No log | 2.1633 | 212 | 0.8099 | 0.6547 | 0.8099 | 0.8999 |
No log | 2.1837 | 214 | 0.8121 | 0.5674 | 0.8121 | 0.9012 |
No log | 2.2041 | 216 | 0.8053 | 0.5932 | 0.8053 | 0.8974 |
No log | 2.2245 | 218 | 0.8046 | 0.6273 | 0.8046 | 0.8970 |
No log | 2.2449 | 220 | 0.7971 | 0.6207 | 0.7971 | 0.8928 |
No log | 2.2653 | 222 | 0.7891 | 0.6017 | 0.7891 | 0.8883 |
No log | 2.2857 | 224 | 0.8009 | 0.6453 | 0.8009 | 0.8950 |
No log | 2.3061 | 226 | 0.8842 | 0.6194 | 0.8842 | 0.9403 |
No log | 2.3265 | 228 | 0.9771 | 0.5717 | 0.9771 | 0.9885 |
No log | 2.3469 | 230 | 0.9543 | 0.5542 | 0.9543 | 0.9769 |
No log | 2.3673 | 232 | 0.8418 | 0.6745 | 0.8418 | 0.9175 |
No log | 2.3878 | 234 | 0.8197 | 0.6634 | 0.8197 | 0.9054 |
No log | 2.4082 | 236 | 0.8413 | 0.6373 | 0.8413 | 0.9172 |
No log | 2.4286 | 238 | 0.9307 | 0.5754 | 0.9307 | 0.9647 |
No log | 2.4490 | 240 | 0.9791 | 0.5705 | 0.9791 | 0.9895 |
No log | 2.4694 | 242 | 0.9951 | 0.5681 | 0.9951 | 0.9976 |
No log | 2.4898 | 244 | 0.8579 | 0.5968 | 0.8579 | 0.9263 |
No log | 2.5102 | 246 | 0.7679 | 0.6500 | 0.7680 | 0.8763 |
No log | 2.5306 | 248 | 0.7751 | 0.6552 | 0.7751 | 0.8804 |
No log | 2.5510 | 250 | 0.7938 | 0.6515 | 0.7938 | 0.8909 |
No log | 2.5714 | 252 | 0.8133 | 0.6893 | 0.8133 | 0.9018 |
No log | 2.5918 | 254 | 0.7939 | 0.7031 | 0.7939 | 0.8910 |
No log | 2.6122 | 256 | 0.8022 | 0.6814 | 0.8022 | 0.8957 |
No log | 2.6327 | 258 | 0.8739 | 0.6110 | 0.8739 | 0.9348 |
No log | 2.6531 | 260 | 0.8748 | 0.6291 | 0.8748 | 0.9353 |
No log | 2.6735 | 262 | 0.8060 | 0.6416 | 0.8060 | 0.8978 |
No log | 2.6939 | 264 | 0.7833 | 0.6327 | 0.7833 | 0.8850 |
No log | 2.7143 | 266 | 0.8106 | 0.6178 | 0.8106 | 0.9004 |
No log | 2.7347 | 268 | 0.7923 | 0.6011 | 0.7923 | 0.8901 |
No log | 2.7551 | 270 | 0.7857 | 0.5275 | 0.7857 | 0.8864 |
No log | 2.7755 | 272 | 0.8094 | 0.5232 | 0.8094 | 0.8996 |
No log | 2.7959 | 274 | 0.8560 | 0.5391 | 0.8560 | 0.9252 |
No log | 2.8163 | 276 | 0.8427 | 0.5945 | 0.8427 | 0.9180 |
No log | 2.8367 | 278 | 0.7787 | 0.6242 | 0.7787 | 0.8825 |
No log | 2.8571 | 280 | 0.7810 | 0.6056 | 0.7810 | 0.8837 |
No log | 2.8776 | 282 | 0.7783 | 0.6472 | 0.7783 | 0.8822 |
No log | 2.8980 | 284 | 0.7922 | 0.6558 | 0.7922 | 0.8900 |
No log | 2.9184 | 286 | 0.8584 | 0.6175 | 0.8584 | 0.9265 |
No log | 2.9388 | 288 | 0.8867 | 0.6152 | 0.8867 | 0.9416 |
No log | 2.9592 | 290 | 0.8638 | 0.5997 | 0.8638 | 0.9294 |
No log | 2.9796 | 292 | 0.7845 | 0.6047 | 0.7845 | 0.8857 |
No log | 3.0 | 294 | 0.7871 | 0.6231 | 0.7871 | 0.8872 |
No log | 3.0204 | 296 | 0.7811 | 0.5452 | 0.7811 | 0.8838 |
No log | 3.0408 | 298 | 0.7686 | 0.5797 | 0.7686 | 0.8767 |
No log | 3.0612 | 300 | 0.7879 | 0.6053 | 0.7879 | 0.8877 |
No log | 3.0816 | 302 | 0.8143 | 0.6169 | 0.8143 | 0.9024 |
No log | 3.1020 | 304 | 0.8526 | 0.5981 | 0.8526 | 0.9234 |
No log | 3.1224 | 306 | 0.9223 | 0.5677 | 0.9223 | 0.9604 |
No log | 3.1429 | 308 | 0.9449 | 0.5728 | 0.9449 | 0.9721 |
No log | 3.1633 | 310 | 0.9781 | 0.5763 | 0.9781 | 0.9890 |
No log | 3.1837 | 312 | 0.9110 | 0.6137 | 0.9110 | 0.9545 |
No log | 3.2041 | 314 | 0.9057 | 0.6042 | 0.9057 | 0.9517 |
No log | 3.2245 | 316 | 0.9161 | 0.5725 | 0.9161 | 0.9571 |
No log | 3.2449 | 318 | 0.8814 | 0.5251 | 0.8814 | 0.9388 |
No log | 3.2653 | 320 | 0.8385 | 0.5535 | 0.8385 | 0.9157 |
No log | 3.2857 | 322 | 0.8280 | 0.5581 | 0.8280 | 0.9100 |
No log | 3.3061 | 324 | 0.8284 | 0.5611 | 0.8284 | 0.9101 |
No log | 3.3265 | 326 | 0.8294 | 0.5937 | 0.8294 | 0.9107 |
No log | 3.3469 | 328 | 0.8245 | 0.5897 | 0.8245 | 0.9080 |
No log | 3.3673 | 330 | 0.9367 | 0.5185 | 0.9367 | 0.9678 |
No log | 3.3878 | 332 | 1.0880 | 0.5096 | 1.0880 | 1.0431 |
No log | 3.4082 | 334 | 1.1714 | 0.4931 | 1.1714 | 1.0823 |
No log | 3.4286 | 336 | 1.0478 | 0.5075 | 1.0478 | 1.0236 |
No log | 3.4490 | 338 | 0.8886 | 0.6146 | 0.8886 | 0.9426 |
No log | 3.4694 | 340 | 0.8356 | 0.6605 | 0.8356 | 0.9141 |
No log | 3.4898 | 342 | 0.8355 | 0.6539 | 0.8355 | 0.9141 |
No log | 3.5102 | 344 | 0.8534 | 0.6248 | 0.8534 | 0.9238 |
No log | 3.5306 | 346 | 0.9956 | 0.5417 | 0.9956 | 0.9978 |
No log | 3.5510 | 348 | 1.0239 | 0.5398 | 1.0239 | 1.0119 |
No log | 3.5714 | 350 | 0.8895 | 0.6229 | 0.8895 | 0.9431 |
No log | 3.5918 | 352 | 0.8105 | 0.6411 | 0.8105 | 0.9003 |
No log | 3.6122 | 354 | 0.8146 | 0.6539 | 0.8146 | 0.9025 |
No log | 3.6327 | 356 | 0.9260 | 0.6215 | 0.9260 | 0.9623 |
No log | 3.6531 | 358 | 1.0002 | 0.5798 | 1.0002 | 1.0001 |
No log | 3.6735 | 360 | 1.0305 | 0.5880 | 1.0305 | 1.0151 |
No log | 3.6939 | 362 | 0.9930 | 0.6113 | 0.9930 | 0.9965 |
No log | 3.7143 | 364 | 1.0737 | 0.5622 | 1.0737 | 1.0362 |
No log | 3.7347 | 366 | 1.3230 | 0.4623 | 1.3230 | 1.1502 |
No log | 3.7551 | 368 | 1.4403 | 0.4469 | 1.4403 | 1.2001 |
No log | 3.7755 | 370 | 1.2831 | 0.4609 | 1.2831 | 1.1327 |
No log | 3.7959 | 372 | 1.0507 | 0.5269 | 1.0507 | 1.0250 |
No log | 3.8163 | 374 | 0.8297 | 0.5934 | 0.8297 | 0.9109 |
No log | 3.8367 | 376 | 0.7816 | 0.6017 | 0.7816 | 0.8841 |
No log | 3.8571 | 378 | 0.8245 | 0.5537 | 0.8245 | 0.9080 |
No log | 3.8776 | 380 | 0.8715 | 0.5647 | 0.8715 | 0.9336 |
No log | 3.8980 | 382 | 0.9330 | 0.5758 | 0.9330 | 0.9659 |
No log | 3.9184 | 384 | 0.9316 | 0.5929 | 0.9316 | 0.9652 |
No log | 3.9388 | 386 | 0.8706 | 0.6051 | 0.8706 | 0.9331 |
No log | 3.9592 | 388 | 0.8987 | 0.6094 | 0.8987 | 0.9480 |
No log | 3.9796 | 390 | 0.9083 | 0.6064 | 0.9083 | 0.9531 |
No log | 4.0 | 392 | 0.9501 | 0.5584 | 0.9501 | 0.9747 |
No log | 4.0204 | 394 | 0.8813 | 0.5906 | 0.8813 | 0.9388 |
No log | 4.0408 | 396 | 0.7753 | 0.5521 | 0.7753 | 0.8805 |
No log | 4.0612 | 398 | 0.7389 | 0.5779 | 0.7389 | 0.8596 |
No log | 4.0816 | 400 | 0.7264 | 0.6057 | 0.7264 | 0.8523 |
No log | 4.1020 | 402 | 0.7115 | 0.6388 | 0.7115 | 0.8435 |
No log | 4.1224 | 404 | 0.7163 | 0.6783 | 0.7163 | 0.8463 |
No log | 4.1429 | 406 | 0.8791 | 0.6098 | 0.8791 | 0.9376 |
No log | 4.1633 | 408 | 1.0036 | 0.5694 | 1.0036 | 1.0018 |
No log | 4.1837 | 410 | 0.9089 | 0.6186 | 0.9089 | 0.9533 |
No log | 4.2041 | 412 | 0.8027 | 0.6618 | 0.8027 | 0.8959 |
No log | 4.2245 | 414 | 0.7292 | 0.6916 | 0.7292 | 0.8539 |
No log | 4.2449 | 416 | 0.7188 | 0.6979 | 0.7188 | 0.8478 |
No log | 4.2653 | 418 | 0.7246 | 0.6854 | 0.7246 | 0.8512 |
No log | 4.2857 | 420 | 0.8110 | 0.6419 | 0.8110 | 0.9006 |
No log | 4.3061 | 422 | 0.8863 | 0.5792 | 0.8863 | 0.9415 |
No log | 4.3265 | 424 | 0.8644 | 0.6068 | 0.8644 | 0.9297 |
No log | 4.3469 | 426 | 0.8395 | 0.6261 | 0.8395 | 0.9162 |
No log | 4.3673 | 428 | 0.8756 | 0.5965 | 0.8756 | 0.9357 |
No log | 4.3878 | 430 | 0.8744 | 0.5921 | 0.8744 | 0.9351 |
No log | 4.4082 | 432 | 0.8075 | 0.6459 | 0.8075 | 0.8986 |
No log | 4.4286 | 434 | 0.7530 | 0.7056 | 0.7530 | 0.8677 |
No log | 4.4490 | 436 | 0.7648 | 0.7082 | 0.7648 | 0.8745 |
No log | 4.4694 | 438 | 0.7714 | 0.7143 | 0.7714 | 0.8783 |
No log | 4.4898 | 440 | 0.8663 | 0.6323 | 0.8663 | 0.9308 |
No log | 4.5102 | 442 | 1.0017 | 0.5389 | 1.0017 | 1.0009 |
No log | 4.5306 | 444 | 1.0013 | 0.5236 | 1.0013 | 1.0006 |
No log | 4.5510 | 446 | 0.8802 | 0.6126 | 0.8802 | 0.9382 |
No log | 4.5714 | 448 | 0.7566 | 0.6297 | 0.7566 | 0.8698 |
No log | 4.5918 | 450 | 0.7435 | 0.6242 | 0.7435 | 0.8623 |
No log | 4.6122 | 452 | 0.7596 | 0.6262 | 0.7596 | 0.8716 |
No log | 4.6327 | 454 | 0.8249 | 0.6373 | 0.8249 | 0.9083 |
No log | 4.6531 | 456 | 0.9342 | 0.5728 | 0.9342 | 0.9665 |
No log | 4.6735 | 458 | 0.9896 | 0.5545 | 0.9896 | 0.9948 |
No log | 4.6939 | 460 | 0.9036 | 0.5739 | 0.9036 | 0.9506 |
No log | 4.7143 | 462 | 0.8331 | 0.6070 | 0.8331 | 0.9127 |
No log | 4.7347 | 464 | 0.8336 | 0.6020 | 0.8336 | 0.9130 |
No log | 4.7551 | 466 | 0.8941 | 0.5315 | 0.8941 | 0.9456 |
No log | 4.7755 | 468 | 0.9204 | 0.5347 | 0.9204 | 0.9593 |
No log | 4.7959 | 470 | 0.9576 | 0.5400 | 0.9576 | 0.9786 |
No log | 4.8163 | 472 | 0.9523 | 0.5547 | 0.9523 | 0.9758 |
No log | 4.8367 | 474 | 0.8500 | 0.5663 | 0.8500 | 0.9220 |
No log | 4.8571 | 476 | 0.7566 | 0.6555 | 0.7566 | 0.8698 |
No log | 4.8776 | 478 | 0.7041 | 0.6414 | 0.7041 | 0.8391 |
No log | 4.8980 | 480 | 0.7045 | 0.6644 | 0.7045 | 0.8393 |
No log | 4.9184 | 482 | 0.7342 | 0.6575 | 0.7342 | 0.8569 |
No log | 4.9388 | 484 | 0.8078 | 0.6360 | 0.8078 | 0.8988 |
No log | 4.9592 | 486 | 0.8087 | 0.6367 | 0.8087 | 0.8993 |
No log | 4.9796 | 488 | 0.8095 | 0.6415 | 0.8095 | 0.8997 |
No log | 5.0 | 490 | 0.7502 | 0.6757 | 0.7502 | 0.8661 |
No log | 5.0204 | 492 | 0.7597 | 0.6511 | 0.7597 | 0.8716 |
No log | 5.0408 | 494 | 0.8037 | 0.6451 | 0.8037 | 0.8965 |
No log | 5.0612 | 496 | 0.7664 | 0.6606 | 0.7664 | 0.8754 |
No log | 5.0816 | 498 | 0.6825 | 0.6747 | 0.6825 | 0.8261 |
0.4171 | 5.1020 | 500 | 0.6675 | 0.6810 | 0.6675 | 0.8170 |
0.4171 | 5.1224 | 502 | 0.6677 | 0.6810 | 0.6677 | 0.8172 |
0.4171 | 5.1429 | 504 | 0.7164 | 0.6902 | 0.7164 | 0.8464 |
0.4171 | 5.1633 | 506 | 0.7852 | 0.6741 | 0.7852 | 0.8861 |
0.4171 | 5.1837 | 508 | 0.8311 | 0.6282 | 0.8311 | 0.9116 |
0.4171 | 5.2041 | 510 | 0.8097 | 0.6385 | 0.8097 | 0.8999 |
0.4171 | 5.2245 | 512 | 0.7317 | 0.6624 | 0.7317 | 0.8554 |
0.4171 | 5.2449 | 514 | 0.6928 | 0.6096 | 0.6928 | 0.8323 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 7
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k20_task1_organization
Base model
aubmindlab/bert-base-arabertv02