ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run2_AugV5_k14_task2_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: 0.8617
- Qwk: 0.4220
- Mse: 0.8617
- Rmse: 0.9283
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 | 0.0392 | 2 | 4.6805 | -0.0132 | 4.6805 | 2.1635 |
No log | 0.0784 | 4 | 2.6738 | -0.0084 | 2.6738 | 1.6352 |
No log | 0.1176 | 6 | 2.4271 | -0.1115 | 2.4271 | 1.5579 |
No log | 0.1569 | 8 | 2.0600 | -0.0017 | 2.0600 | 1.4353 |
No log | 0.1961 | 10 | 1.3955 | 0.0661 | 1.3955 | 1.1813 |
No log | 0.2353 | 12 | 1.2844 | 0.0561 | 1.2844 | 1.1333 |
No log | 0.2745 | 14 | 1.3536 | 0.0488 | 1.3536 | 1.1634 |
No log | 0.3137 | 16 | 1.4246 | 0.0488 | 1.4246 | 1.1935 |
No log | 0.3529 | 18 | 1.5773 | 0.0 | 1.5773 | 1.2559 |
No log | 0.3922 | 20 | 1.6455 | 0.0169 | 1.6455 | 1.2828 |
No log | 0.4314 | 22 | 1.3891 | 0.0038 | 1.3891 | 1.1786 |
No log | 0.4706 | 24 | 1.3973 | -0.0132 | 1.3973 | 1.1821 |
No log | 0.5098 | 26 | 1.4647 | -0.0132 | 1.4647 | 1.2102 |
No log | 0.5490 | 28 | 1.2120 | 0.2245 | 1.2120 | 1.1009 |
No log | 0.5882 | 30 | 1.1904 | 0.2342 | 1.1904 | 1.0911 |
No log | 0.6275 | 32 | 1.3581 | 0.0600 | 1.3581 | 1.1654 |
No log | 0.6667 | 34 | 1.3790 | 0.0600 | 1.3790 | 1.1743 |
No log | 0.7059 | 36 | 1.3767 | 0.0750 | 1.3767 | 1.1733 |
No log | 0.7451 | 38 | 1.4080 | 0.0750 | 1.4080 | 1.1866 |
No log | 0.7843 | 40 | 1.3509 | 0.1495 | 1.3509 | 1.1623 |
No log | 0.8235 | 42 | 1.2776 | 0.2108 | 1.2776 | 1.1303 |
No log | 0.8627 | 44 | 1.2322 | 0.1904 | 1.2322 | 1.1100 |
No log | 0.9020 | 46 | 1.3957 | 0.0955 | 1.3957 | 1.1814 |
No log | 0.9412 | 48 | 1.5660 | 0.0310 | 1.5660 | 1.2514 |
No log | 0.9804 | 50 | 1.4056 | 0.1842 | 1.4056 | 1.1856 |
No log | 1.0196 | 52 | 1.3778 | 0.2377 | 1.3778 | 1.1738 |
No log | 1.0588 | 54 | 1.3796 | 0.2544 | 1.3796 | 1.1745 |
No log | 1.0980 | 56 | 1.2416 | 0.2149 | 1.2416 | 1.1143 |
No log | 1.1373 | 58 | 1.1237 | 0.2537 | 1.1237 | 1.0601 |
No log | 1.1765 | 60 | 1.1783 | 0.2374 | 1.1783 | 1.0855 |
No log | 1.2157 | 62 | 1.2600 | 0.2283 | 1.2600 | 1.1225 |
No log | 1.2549 | 64 | 1.2494 | 0.1638 | 1.2494 | 1.1178 |
No log | 1.2941 | 66 | 1.1574 | 0.2167 | 1.1574 | 1.0758 |
No log | 1.3333 | 68 | 1.1305 | 0.2167 | 1.1305 | 1.0632 |
No log | 1.3725 | 70 | 1.1658 | 0.2532 | 1.1658 | 1.0797 |
No log | 1.4118 | 72 | 1.3829 | 0.1738 | 1.3829 | 1.1760 |
No log | 1.4510 | 74 | 1.5409 | 0.1457 | 1.5409 | 1.2413 |
No log | 1.4902 | 76 | 1.7079 | 0.0800 | 1.7079 | 1.3069 |
No log | 1.5294 | 78 | 1.6392 | 0.0568 | 1.6392 | 1.2803 |
No log | 1.5686 | 80 | 1.3314 | 0.1438 | 1.3314 | 1.1539 |
No log | 1.6078 | 82 | 1.1382 | 0.2589 | 1.1382 | 1.0669 |
No log | 1.6471 | 84 | 1.0333 | 0.3195 | 1.0333 | 1.0165 |
No log | 1.6863 | 86 | 1.0151 | 0.3404 | 1.0151 | 1.0075 |
No log | 1.7255 | 88 | 1.0314 | 0.2938 | 1.0314 | 1.0156 |
No log | 1.7647 | 90 | 1.1807 | 0.2095 | 1.1807 | 1.0866 |
No log | 1.8039 | 92 | 1.6365 | 0.1117 | 1.6365 | 1.2793 |
No log | 1.8431 | 94 | 2.2214 | 0.1489 | 2.2214 | 1.4904 |
No log | 1.8824 | 96 | 2.3773 | 0.1258 | 2.3773 | 1.5419 |
No log | 1.9216 | 98 | 2.1821 | 0.2008 | 2.1821 | 1.4772 |
No log | 1.9608 | 100 | 1.8052 | 0.2012 | 1.8052 | 1.3436 |
No log | 2.0 | 102 | 1.3041 | 0.1535 | 1.3041 | 1.1420 |
No log | 2.0392 | 104 | 1.0108 | 0.2738 | 1.0108 | 1.0054 |
No log | 2.0784 | 106 | 0.9505 | 0.4033 | 0.9505 | 0.9749 |
No log | 2.1176 | 108 | 0.8971 | 0.4645 | 0.8971 | 0.9471 |
No log | 2.1569 | 110 | 0.8907 | 0.4645 | 0.8907 | 0.9438 |
No log | 2.1961 | 112 | 0.9243 | 0.4197 | 0.9243 | 0.9614 |
No log | 2.2353 | 114 | 1.0148 | 0.3613 | 1.0148 | 1.0073 |
No log | 2.2745 | 116 | 1.0794 | 0.3484 | 1.0794 | 1.0390 |
No log | 2.3137 | 118 | 1.0855 | 0.3584 | 1.0855 | 1.0419 |
No log | 2.3529 | 120 | 1.0386 | 0.3798 | 1.0386 | 1.0191 |
No log | 2.3922 | 122 | 0.9869 | 0.3837 | 0.9869 | 0.9934 |
No log | 2.4314 | 124 | 1.0951 | 0.3363 | 1.0951 | 1.0465 |
No log | 2.4706 | 126 | 1.0979 | 0.2734 | 1.0979 | 1.0478 |
No log | 2.5098 | 128 | 1.1317 | 0.3416 | 1.1317 | 1.0638 |
No log | 2.5490 | 130 | 1.1018 | 0.2734 | 1.1018 | 1.0496 |
No log | 2.5882 | 132 | 1.0157 | 0.3117 | 1.0157 | 1.0078 |
No log | 2.6275 | 134 | 0.9381 | 0.4549 | 0.9381 | 0.9686 |
No log | 2.6667 | 136 | 0.9465 | 0.4549 | 0.9465 | 0.9729 |
No log | 2.7059 | 138 | 0.9773 | 0.3841 | 0.9773 | 0.9886 |
No log | 2.7451 | 140 | 0.9099 | 0.4368 | 0.9099 | 0.9539 |
No log | 2.7843 | 142 | 0.8638 | 0.4527 | 0.8638 | 0.9294 |
No log | 2.8235 | 144 | 0.8544 | 0.4637 | 0.8544 | 0.9244 |
No log | 2.8627 | 146 | 0.9392 | 0.4703 | 0.9392 | 0.9691 |
No log | 2.9020 | 148 | 0.9266 | 0.5333 | 0.9266 | 0.9626 |
No log | 2.9412 | 150 | 0.8093 | 0.6167 | 0.8093 | 0.8996 |
No log | 2.9804 | 152 | 0.8601 | 0.4175 | 0.8601 | 0.9274 |
No log | 3.0196 | 154 | 0.9404 | 0.3287 | 0.9404 | 0.9698 |
No log | 3.0588 | 156 | 0.9617 | 0.3149 | 0.9617 | 0.9807 |
No log | 3.0980 | 158 | 0.9668 | 0.4591 | 0.9668 | 0.9833 |
No log | 3.1373 | 160 | 0.9711 | 0.4691 | 0.9711 | 0.9855 |
No log | 3.1765 | 162 | 0.9248 | 0.4681 | 0.9248 | 0.9617 |
No log | 3.2157 | 164 | 0.8787 | 0.5458 | 0.8787 | 0.9374 |
No log | 3.2549 | 166 | 0.8352 | 0.5526 | 0.8352 | 0.9139 |
No log | 3.2941 | 168 | 0.8331 | 0.5756 | 0.8331 | 0.9128 |
No log | 3.3333 | 170 | 0.9259 | 0.5147 | 0.9259 | 0.9623 |
No log | 3.3725 | 172 | 0.8950 | 0.5154 | 0.8950 | 0.9461 |
No log | 3.4118 | 174 | 1.0169 | 0.3385 | 1.0169 | 1.0084 |
No log | 3.4510 | 176 | 1.3691 | 0.3001 | 1.3691 | 1.1701 |
No log | 3.4902 | 178 | 1.2906 | 0.3702 | 1.2906 | 1.1361 |
No log | 3.5294 | 180 | 1.0114 | 0.3521 | 1.0114 | 1.0057 |
No log | 3.5686 | 182 | 0.8751 | 0.4626 | 0.8751 | 0.9355 |
No log | 3.6078 | 184 | 0.8740 | 0.5329 | 0.8740 | 0.9349 |
No log | 3.6471 | 186 | 0.8692 | 0.5155 | 0.8692 | 0.9323 |
No log | 3.6863 | 188 | 0.9598 | 0.3149 | 0.9598 | 0.9797 |
No log | 3.7255 | 190 | 1.0935 | 0.3410 | 1.0936 | 1.0457 |
No log | 3.7647 | 192 | 1.0933 | 0.4267 | 1.0933 | 1.0456 |
No log | 3.8039 | 194 | 0.9682 | 0.4303 | 0.9682 | 0.9840 |
No log | 3.8431 | 196 | 0.9472 | 0.4626 | 0.9472 | 0.9733 |
No log | 3.8824 | 198 | 0.9848 | 0.3374 | 0.9848 | 0.9924 |
No log | 3.9216 | 200 | 1.0061 | 0.3758 | 1.0061 | 1.0030 |
No log | 3.9608 | 202 | 1.0043 | 0.4699 | 1.0043 | 1.0022 |
No log | 4.0 | 204 | 1.0780 | 0.4119 | 1.0780 | 1.0382 |
No log | 4.0392 | 206 | 1.0010 | 0.4556 | 1.0010 | 1.0005 |
No log | 4.0784 | 208 | 0.9168 | 0.4826 | 0.9168 | 0.9575 |
No log | 4.1176 | 210 | 0.9659 | 0.4334 | 0.9659 | 0.9828 |
No log | 4.1569 | 212 | 0.9399 | 0.4775 | 0.9399 | 0.9695 |
No log | 4.1961 | 214 | 0.8783 | 0.4879 | 0.8783 | 0.9372 |
No log | 4.2353 | 216 | 0.8624 | 0.4930 | 0.8624 | 0.9287 |
No log | 4.2745 | 218 | 0.8706 | 0.5283 | 0.8706 | 0.9331 |
No log | 4.3137 | 220 | 0.8888 | 0.5450 | 0.8888 | 0.9428 |
No log | 4.3529 | 222 | 1.0378 | 0.3990 | 1.0378 | 1.0187 |
No log | 4.3922 | 224 | 1.1014 | 0.3673 | 1.1014 | 1.0495 |
No log | 4.4314 | 226 | 1.0202 | 0.4286 | 1.0202 | 1.0101 |
No log | 4.4706 | 228 | 0.8880 | 0.5450 | 0.8880 | 0.9423 |
No log | 4.5098 | 230 | 0.8636 | 0.5058 | 0.8636 | 0.9293 |
No log | 4.5490 | 232 | 0.8895 | 0.5291 | 0.8895 | 0.9431 |
No log | 4.5882 | 234 | 0.8942 | 0.5291 | 0.8942 | 0.9456 |
No log | 4.6275 | 236 | 0.8422 | 0.4789 | 0.8422 | 0.9177 |
No log | 4.6667 | 238 | 0.8856 | 0.5259 | 0.8856 | 0.9411 |
No log | 4.7059 | 240 | 0.9355 | 0.4662 | 0.9355 | 0.9672 |
No log | 4.7451 | 242 | 0.9534 | 0.4346 | 0.9534 | 0.9764 |
No log | 4.7843 | 244 | 0.9926 | 0.3945 | 0.9926 | 0.9963 |
No log | 4.8235 | 246 | 1.0758 | 0.3918 | 1.0758 | 1.0372 |
No log | 4.8627 | 248 | 1.0341 | 0.3465 | 1.0341 | 1.0169 |
No log | 4.9020 | 250 | 1.0061 | 0.4444 | 1.0061 | 1.0030 |
No log | 4.9412 | 252 | 1.0022 | 0.4256 | 1.0022 | 1.0011 |
No log | 4.9804 | 254 | 1.0061 | 0.4450 | 1.0061 | 1.0030 |
No log | 5.0196 | 256 | 1.0082 | 0.3794 | 1.0082 | 1.0041 |
No log | 5.0588 | 258 | 1.0095 | 0.3794 | 1.0095 | 1.0048 |
No log | 5.0980 | 260 | 1.0098 | 0.4346 | 1.0098 | 1.0049 |
No log | 5.1373 | 262 | 1.0904 | 0.4050 | 1.0904 | 1.0442 |
No log | 5.1765 | 264 | 1.1586 | 0.3826 | 1.1586 | 1.0764 |
No log | 5.2157 | 266 | 1.1098 | 0.3933 | 1.1098 | 1.0535 |
No log | 5.2549 | 268 | 1.0723 | 0.3708 | 1.0723 | 1.0355 |
No log | 5.2941 | 270 | 1.0672 | 0.3326 | 1.0672 | 1.0331 |
No log | 5.3333 | 272 | 1.0333 | 0.3998 | 1.0333 | 1.0165 |
No log | 5.3725 | 274 | 1.0074 | 0.3155 | 1.0074 | 1.0037 |
No log | 5.4118 | 276 | 0.9641 | 0.3938 | 0.9641 | 0.9819 |
No log | 5.4510 | 278 | 0.9424 | 0.4369 | 0.9424 | 0.9708 |
No log | 5.4902 | 280 | 0.9287 | 0.4527 | 0.9287 | 0.9637 |
No log | 5.5294 | 282 | 0.9250 | 0.4374 | 0.9250 | 0.9618 |
No log | 5.5686 | 284 | 0.9248 | 0.4125 | 0.9248 | 0.9617 |
No log | 5.6078 | 286 | 0.9373 | 0.3957 | 0.9373 | 0.9681 |
No log | 5.6471 | 288 | 0.9111 | 0.4964 | 0.9111 | 0.9545 |
No log | 5.6863 | 290 | 0.9393 | 0.4176 | 0.9393 | 0.9692 |
No log | 5.7255 | 292 | 0.9243 | 0.4176 | 0.9243 | 0.9614 |
No log | 5.7647 | 294 | 0.8929 | 0.4256 | 0.8929 | 0.9449 |
No log | 5.8039 | 296 | 0.9299 | 0.4579 | 0.9299 | 0.9643 |
No log | 5.8431 | 298 | 0.9399 | 0.4785 | 0.9399 | 0.9695 |
No log | 5.8824 | 300 | 0.9113 | 0.4593 | 0.9113 | 0.9546 |
No log | 5.9216 | 302 | 0.9508 | 0.5253 | 0.9508 | 0.9751 |
No log | 5.9608 | 304 | 0.9091 | 0.4514 | 0.9091 | 0.9535 |
No log | 6.0 | 306 | 0.9063 | 0.5029 | 0.9063 | 0.9520 |
No log | 6.0392 | 308 | 0.9690 | 0.4510 | 0.9690 | 0.9844 |
No log | 6.0784 | 310 | 0.9085 | 0.5073 | 0.9085 | 0.9531 |
No log | 6.1176 | 312 | 0.8337 | 0.4801 | 0.8337 | 0.9131 |
No log | 6.1569 | 314 | 0.8375 | 0.4801 | 0.8375 | 0.9151 |
No log | 6.1961 | 316 | 0.8534 | 0.4705 | 0.8534 | 0.9238 |
No log | 6.2353 | 318 | 0.8730 | 0.4705 | 0.8730 | 0.9344 |
No log | 6.2745 | 320 | 0.9101 | 0.4256 | 0.9101 | 0.9540 |
No log | 6.3137 | 322 | 0.9366 | 0.3788 | 0.9366 | 0.9678 |
No log | 6.3529 | 324 | 0.9344 | 0.3788 | 0.9344 | 0.9667 |
No log | 6.3922 | 326 | 0.9331 | 0.3987 | 0.9331 | 0.9659 |
No log | 6.4314 | 328 | 0.9874 | 0.4202 | 0.9874 | 0.9937 |
No log | 6.4706 | 330 | 0.9828 | 0.4439 | 0.9828 | 0.9914 |
No log | 6.5098 | 332 | 0.9404 | 0.2694 | 0.9404 | 0.9697 |
No log | 6.5490 | 334 | 0.9505 | 0.3263 | 0.9505 | 0.9750 |
No log | 6.5882 | 336 | 0.9790 | 0.3411 | 0.9790 | 0.9894 |
No log | 6.6275 | 338 | 0.9523 | 0.3263 | 0.9523 | 0.9758 |
No log | 6.6667 | 340 | 0.9440 | 0.3596 | 0.9440 | 0.9716 |
No log | 6.7059 | 342 | 0.9433 | 0.3210 | 0.9433 | 0.9713 |
No log | 6.7451 | 344 | 0.9198 | 0.3066 | 0.9198 | 0.9591 |
No log | 6.7843 | 346 | 0.9323 | 0.3660 | 0.9323 | 0.9656 |
No log | 6.8235 | 348 | 0.9351 | 0.3457 | 0.9351 | 0.9670 |
No log | 6.8627 | 350 | 0.9322 | 0.3373 | 0.9322 | 0.9655 |
No log | 6.9020 | 352 | 0.8893 | 0.3671 | 0.8893 | 0.9430 |
No log | 6.9412 | 354 | 0.9043 | 0.4142 | 0.9043 | 0.9509 |
No log | 6.9804 | 356 | 0.9357 | 0.4568 | 0.9357 | 0.9673 |
No log | 7.0196 | 358 | 0.9564 | 0.3493 | 0.9564 | 0.9779 |
No log | 7.0588 | 360 | 0.9921 | 0.3346 | 0.9921 | 0.9960 |
No log | 7.0980 | 362 | 0.9973 | 0.3205 | 0.9973 | 0.9987 |
No log | 7.1373 | 364 | 0.9874 | 0.3210 | 0.9874 | 0.9937 |
No log | 7.1765 | 366 | 0.9682 | 0.3089 | 0.9682 | 0.9840 |
No log | 7.2157 | 368 | 0.9548 | 0.3608 | 0.9548 | 0.9771 |
No log | 7.2549 | 370 | 0.9605 | 0.3527 | 0.9605 | 0.9801 |
No log | 7.2941 | 372 | 0.9659 | 0.3527 | 0.9659 | 0.9828 |
No log | 7.3333 | 374 | 0.9913 | 0.3457 | 0.9913 | 0.9957 |
No log | 7.3725 | 376 | 0.9668 | 0.3513 | 0.9668 | 0.9833 |
No log | 7.4118 | 378 | 0.9586 | 0.3804 | 0.9586 | 0.9791 |
No log | 7.4510 | 380 | 1.0024 | 0.4264 | 1.0024 | 1.0012 |
No log | 7.4902 | 382 | 0.9607 | 0.3804 | 0.9607 | 0.9802 |
No log | 7.5294 | 384 | 0.9158 | 0.3145 | 0.9158 | 0.9570 |
No log | 7.5686 | 386 | 0.9633 | 0.3590 | 0.9633 | 0.9815 |
No log | 7.6078 | 388 | 1.0783 | 0.3523 | 1.0783 | 1.0384 |
No log | 7.6471 | 390 | 1.0783 | 0.3784 | 1.0783 | 1.0384 |
No log | 7.6863 | 392 | 0.9584 | 0.4175 | 0.9584 | 0.9790 |
No log | 7.7255 | 394 | 0.8756 | 0.4120 | 0.8756 | 0.9357 |
No log | 7.7647 | 396 | 0.8678 | 0.4045 | 0.8678 | 0.9316 |
No log | 7.8039 | 398 | 0.8712 | 0.3896 | 0.8712 | 0.9334 |
No log | 7.8431 | 400 | 0.8655 | 0.3685 | 0.8655 | 0.9303 |
No log | 7.8824 | 402 | 0.8747 | 0.3263 | 0.8747 | 0.9352 |
No log | 7.9216 | 404 | 0.9072 | 0.3502 | 0.9072 | 0.9525 |
No log | 7.9608 | 406 | 0.8933 | 0.3602 | 0.8933 | 0.9452 |
No log | 8.0 | 408 | 0.8742 | 0.3263 | 0.8742 | 0.9350 |
No log | 8.0392 | 410 | 0.8725 | 0.3674 | 0.8725 | 0.9341 |
No log | 8.0784 | 412 | 0.8732 | 0.3570 | 0.8732 | 0.9345 |
No log | 8.1176 | 414 | 0.8779 | 0.3263 | 0.8779 | 0.9370 |
No log | 8.1569 | 416 | 0.8899 | 0.3062 | 0.8899 | 0.9433 |
No log | 8.1961 | 418 | 0.8990 | 0.3263 | 0.8990 | 0.9481 |
No log | 8.2353 | 420 | 0.9068 | 0.3216 | 0.9068 | 0.9523 |
No log | 8.2745 | 422 | 0.9033 | 0.3318 | 0.9033 | 0.9504 |
No log | 8.3137 | 424 | 0.8974 | 0.3216 | 0.8974 | 0.9473 |
No log | 8.3529 | 426 | 0.9018 | 0.3216 | 0.9018 | 0.9496 |
No log | 8.3922 | 428 | 0.9219 | 0.3163 | 0.9219 | 0.9602 |
No log | 8.4314 | 430 | 0.9715 | 0.3657 | 0.9715 | 0.9856 |
No log | 8.4706 | 432 | 1.0289 | 0.3699 | 1.0289 | 1.0143 |
No log | 8.5098 | 434 | 0.9977 | 0.2963 | 0.9977 | 0.9989 |
No log | 8.5490 | 436 | 0.9753 | 0.3066 | 0.9753 | 0.9876 |
No log | 8.5882 | 438 | 0.9870 | 0.3119 | 0.9870 | 0.9935 |
No log | 8.6275 | 440 | 0.9835 | 0.2038 | 0.9835 | 0.9917 |
No log | 8.6667 | 442 | 0.9567 | 0.3271 | 0.9567 | 0.9781 |
No log | 8.7059 | 444 | 0.9574 | 0.3747 | 0.9574 | 0.9785 |
No log | 8.7451 | 446 | 1.0043 | 0.3646 | 1.0043 | 1.0021 |
No log | 8.7843 | 448 | 0.9759 | 0.3646 | 0.9759 | 0.9879 |
No log | 8.8235 | 450 | 0.9136 | 0.3855 | 0.9136 | 0.9558 |
No log | 8.8627 | 452 | 0.8976 | 0.4505 | 0.8976 | 0.9474 |
No log | 8.9020 | 454 | 0.9082 | 0.4275 | 0.9082 | 0.9530 |
No log | 8.9412 | 456 | 0.8806 | 0.4278 | 0.8806 | 0.9384 |
No log | 8.9804 | 458 | 0.8760 | 0.4661 | 0.8759 | 0.9359 |
No log | 9.0196 | 460 | 0.8798 | 0.4563 | 0.8798 | 0.9380 |
No log | 9.0588 | 462 | 0.8626 | 0.4726 | 0.8626 | 0.9288 |
No log | 9.0980 | 464 | 0.8729 | 0.4413 | 0.8729 | 0.9343 |
No log | 9.1373 | 466 | 0.8975 | 0.3908 | 0.8975 | 0.9474 |
No log | 9.1765 | 468 | 0.9058 | 0.3908 | 0.9058 | 0.9518 |
No log | 9.2157 | 470 | 0.8940 | 0.3908 | 0.8940 | 0.9455 |
No log | 9.2549 | 472 | 0.8958 | 0.3908 | 0.8958 | 0.9465 |
No log | 9.2941 | 474 | 0.8909 | 0.4181 | 0.8909 | 0.9439 |
No log | 9.3333 | 476 | 0.9024 | 0.4181 | 0.9024 | 0.9499 |
No log | 9.3725 | 478 | 0.9124 | 0.4181 | 0.9124 | 0.9552 |
No log | 9.4118 | 480 | 0.9377 | 0.4045 | 0.9377 | 0.9683 |
No log | 9.4510 | 482 | 0.9634 | 0.4002 | 0.9634 | 0.9815 |
No log | 9.4902 | 484 | 0.9615 | 0.3243 | 0.9615 | 0.9806 |
No log | 9.5294 | 486 | 0.9603 | 0.3629 | 0.9603 | 0.9799 |
No log | 9.5686 | 488 | 0.9495 | 0.3629 | 0.9495 | 0.9744 |
No log | 9.6078 | 490 | 0.9442 | 0.3685 | 0.9442 | 0.9717 |
No log | 9.6471 | 492 | 0.9334 | 0.3728 | 0.9334 | 0.9661 |
No log | 9.6863 | 494 | 0.9382 | 0.3571 | 0.9382 | 0.9686 |
No log | 9.7255 | 496 | 0.9345 | 0.4059 | 0.9345 | 0.9667 |
No log | 9.7647 | 498 | 0.9132 | 0.4294 | 0.9132 | 0.9556 |
0.367 | 9.8039 | 500 | 0.8974 | 0.4637 | 0.8974 | 0.9473 |
0.367 | 9.8431 | 502 | 0.8946 | 0.5062 | 0.8946 | 0.9458 |
0.367 | 9.8824 | 504 | 0.8746 | 0.4745 | 0.8746 | 0.9352 |
0.367 | 9.9216 | 506 | 0.8645 | 0.5112 | 0.8645 | 0.9298 |
0.367 | 9.9608 | 508 | 0.8611 | 0.4428 | 0.8611 | 0.9279 |
0.367 | 10.0 | 510 | 0.8719 | 0.4077 | 0.8719 | 0.9337 |
0.367 | 10.0392 | 512 | 0.8851 | 0.4533 | 0.8851 | 0.9408 |
0.367 | 10.0784 | 514 | 0.8804 | 0.4428 | 0.8804 | 0.9383 |
0.367 | 10.1176 | 516 | 0.8617 | 0.4220 | 0.8617 | 0.9283 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 2
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
Model tree for MayBashendy/ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run2_AugV5_k14_task2_organization
Base model
aubmindlab/bert-base-arabertv02