ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run999_AugV5_k10_task7_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: 0.5531
- Qwk: 0.4526
- Mse: 0.5531
- Rmse: 0.7437
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 | 0.0364 | 2 | 2.6000 | -0.0084 | 2.6000 | 1.6124 |
No log | 0.0727 | 4 | 1.2395 | 0.0994 | 1.2395 | 1.1133 |
No log | 0.1091 | 6 | 0.9318 | -0.0970 | 0.9318 | 0.9653 |
No log | 0.1455 | 8 | 0.8602 | 0.1628 | 0.8602 | 0.9275 |
No log | 0.1818 | 10 | 0.7642 | 0.2722 | 0.7642 | 0.8742 |
No log | 0.2182 | 12 | 0.8290 | 0.3261 | 0.8290 | 0.9105 |
No log | 0.2545 | 14 | 0.7337 | 0.1308 | 0.7337 | 0.8565 |
No log | 0.2909 | 16 | 0.7062 | 0.2007 | 0.7062 | 0.8404 |
No log | 0.3273 | 18 | 0.7674 | 0.4412 | 0.7674 | 0.8760 |
No log | 0.3636 | 20 | 0.7125 | 0.4412 | 0.7125 | 0.8441 |
No log | 0.4 | 22 | 0.7741 | 0.3371 | 0.7741 | 0.8798 |
No log | 0.4364 | 24 | 0.9811 | 0.2806 | 0.9811 | 0.9905 |
No log | 0.4727 | 26 | 0.7108 | 0.4444 | 0.7108 | 0.8431 |
No log | 0.5091 | 28 | 0.5763 | 0.4517 | 0.5763 | 0.7591 |
No log | 0.5455 | 30 | 0.6046 | 0.4302 | 0.6046 | 0.7776 |
No log | 0.5818 | 32 | 0.5421 | 0.5089 | 0.5421 | 0.7363 |
No log | 0.6182 | 34 | 0.6588 | 0.5131 | 0.6588 | 0.8117 |
No log | 0.6545 | 36 | 0.8622 | 0.3019 | 0.8622 | 0.9286 |
No log | 0.6909 | 38 | 0.7942 | 0.3799 | 0.7942 | 0.8912 |
No log | 0.7273 | 40 | 0.7055 | 0.4502 | 0.7055 | 0.8399 |
No log | 0.7636 | 42 | 0.6951 | 0.2182 | 0.6951 | 0.8337 |
No log | 0.8 | 44 | 0.6869 | 0.1697 | 0.6869 | 0.8288 |
No log | 0.8364 | 46 | 0.6318 | 0.3443 | 0.6318 | 0.7949 |
No log | 0.8727 | 48 | 0.6271 | 0.2038 | 0.6271 | 0.7919 |
No log | 0.9091 | 50 | 0.6922 | 0.3023 | 0.6922 | 0.8320 |
No log | 0.9455 | 52 | 0.5976 | 0.4441 | 0.5976 | 0.7730 |
No log | 0.9818 | 54 | 0.6012 | 0.4595 | 0.6012 | 0.7754 |
No log | 1.0182 | 56 | 0.6577 | 0.4190 | 0.6577 | 0.8110 |
No log | 1.0545 | 58 | 0.8560 | 0.3719 | 0.8560 | 0.9252 |
No log | 1.0909 | 60 | 1.0749 | 0.3129 | 1.0749 | 1.0368 |
No log | 1.1273 | 62 | 1.0215 | 0.2935 | 1.0215 | 1.0107 |
No log | 1.1636 | 64 | 0.7183 | 0.3677 | 0.7183 | 0.8475 |
No log | 1.2 | 66 | 0.6312 | 0.4555 | 0.6312 | 0.7945 |
No log | 1.2364 | 68 | 0.6431 | 0.3914 | 0.6431 | 0.8019 |
No log | 1.2727 | 70 | 0.9106 | 0.3425 | 0.9106 | 0.9542 |
No log | 1.3091 | 72 | 1.2157 | 0.2346 | 1.2157 | 1.1026 |
No log | 1.3455 | 74 | 1.1075 | 0.2880 | 1.1075 | 1.0524 |
No log | 1.3818 | 76 | 0.9433 | 0.3214 | 0.9433 | 0.9712 |
No log | 1.4182 | 78 | 0.6729 | 0.4281 | 0.6729 | 0.8203 |
No log | 1.4545 | 80 | 0.6579 | 0.4655 | 0.6579 | 0.8111 |
No log | 1.4909 | 82 | 0.6667 | 0.3831 | 0.6667 | 0.8165 |
No log | 1.5273 | 84 | 0.5816 | 0.5235 | 0.5816 | 0.7626 |
No log | 1.5636 | 86 | 0.6708 | 0.4014 | 0.6708 | 0.8190 |
No log | 1.6 | 88 | 0.7312 | 0.4627 | 0.7312 | 0.8551 |
No log | 1.6364 | 90 | 0.6696 | 0.4444 | 0.6696 | 0.8183 |
No log | 1.6727 | 92 | 0.6140 | 0.4864 | 0.6140 | 0.7836 |
No log | 1.7091 | 94 | 0.5767 | 0.5071 | 0.5767 | 0.7594 |
No log | 1.7455 | 96 | 0.5839 | 0.4596 | 0.5839 | 0.7641 |
No log | 1.7818 | 98 | 0.6337 | 0.5123 | 0.6337 | 0.7960 |
No log | 1.8182 | 100 | 0.7348 | 0.4197 | 0.7348 | 0.8572 |
No log | 1.8545 | 102 | 0.7717 | 0.4014 | 0.7717 | 0.8785 |
No log | 1.8909 | 104 | 0.7010 | 0.3519 | 0.7010 | 0.8372 |
No log | 1.9273 | 106 | 0.6171 | 0.4136 | 0.6171 | 0.7855 |
No log | 1.9636 | 108 | 0.6141 | 0.3289 | 0.6141 | 0.7836 |
No log | 2.0 | 110 | 0.6052 | 0.4816 | 0.6052 | 0.7779 |
No log | 2.0364 | 112 | 0.7318 | 0.3384 | 0.7318 | 0.8554 |
No log | 2.0727 | 114 | 0.8716 | 0.3636 | 0.8716 | 0.9336 |
No log | 2.1091 | 116 | 0.7752 | 0.4741 | 0.7752 | 0.8805 |
No log | 2.1455 | 118 | 0.6242 | 0.4819 | 0.6242 | 0.7901 |
No log | 2.1818 | 120 | 0.6057 | 0.4901 | 0.6057 | 0.7782 |
No log | 2.2182 | 122 | 0.6010 | 0.4819 | 0.6010 | 0.7753 |
No log | 2.2545 | 124 | 0.6003 | 0.4819 | 0.6003 | 0.7748 |
No log | 2.2909 | 126 | 0.5732 | 0.5604 | 0.5732 | 0.7571 |
No log | 2.3273 | 128 | 0.5711 | 0.5533 | 0.5711 | 0.7557 |
No log | 2.3636 | 130 | 0.5873 | 0.4919 | 0.5873 | 0.7664 |
No log | 2.4 | 132 | 0.6105 | 0.5411 | 0.6105 | 0.7814 |
No log | 2.4364 | 134 | 0.5899 | 0.4901 | 0.5899 | 0.7680 |
No log | 2.4727 | 136 | 0.5826 | 0.4919 | 0.5826 | 0.7633 |
No log | 2.5091 | 138 | 0.5722 | 0.5184 | 0.5722 | 0.7564 |
No log | 2.5455 | 140 | 0.5880 | 0.5336 | 0.5880 | 0.7668 |
No log | 2.5818 | 142 | 0.5773 | 0.5118 | 0.5773 | 0.7598 |
No log | 2.6182 | 144 | 0.5886 | 0.5118 | 0.5886 | 0.7672 |
No log | 2.6545 | 146 | 0.5929 | 0.4782 | 0.5929 | 0.7700 |
No log | 2.6909 | 148 | 0.5806 | 0.4535 | 0.5806 | 0.7620 |
No log | 2.7273 | 150 | 0.5390 | 0.4596 | 0.5390 | 0.7341 |
No log | 2.7636 | 152 | 0.5344 | 0.4591 | 0.5344 | 0.7310 |
No log | 2.8 | 154 | 0.5399 | 0.4726 | 0.5399 | 0.7348 |
No log | 2.8364 | 156 | 0.5687 | 0.5036 | 0.5687 | 0.7541 |
No log | 2.8727 | 158 | 0.5522 | 0.4747 | 0.5522 | 0.7431 |
No log | 2.9091 | 160 | 0.5516 | 0.4747 | 0.5516 | 0.7427 |
No log | 2.9455 | 162 | 0.6043 | 0.5104 | 0.6043 | 0.7774 |
No log | 2.9818 | 164 | 0.5941 | 0.5034 | 0.5941 | 0.7708 |
No log | 3.0182 | 166 | 0.5601 | 0.5373 | 0.5601 | 0.7484 |
No log | 3.0545 | 168 | 0.5983 | 0.5195 | 0.5983 | 0.7735 |
No log | 3.0909 | 170 | 0.5719 | 0.5596 | 0.5719 | 0.7562 |
No log | 3.1273 | 172 | 0.6122 | 0.4596 | 0.6122 | 0.7824 |
No log | 3.1636 | 174 | 0.6628 | 0.5435 | 0.6628 | 0.8141 |
No log | 3.2 | 176 | 0.5844 | 0.5089 | 0.5844 | 0.7644 |
No log | 3.2364 | 178 | 0.5276 | 0.5596 | 0.5276 | 0.7263 |
No log | 3.2727 | 180 | 0.5242 | 0.5390 | 0.5242 | 0.7240 |
No log | 3.3091 | 182 | 0.5251 | 0.4942 | 0.5251 | 0.7246 |
No log | 3.3455 | 184 | 0.5152 | 0.5522 | 0.5152 | 0.7178 |
No log | 3.3818 | 186 | 0.5591 | 0.4979 | 0.5591 | 0.7477 |
No log | 3.4182 | 188 | 0.6609 | 0.5265 | 0.6609 | 0.8130 |
No log | 3.4545 | 190 | 0.5739 | 0.4850 | 0.5739 | 0.7575 |
No log | 3.4909 | 192 | 0.5047 | 0.5195 | 0.5047 | 0.7104 |
No log | 3.5273 | 194 | 0.5328 | 0.5214 | 0.5328 | 0.7299 |
No log | 3.5636 | 196 | 0.5083 | 0.5268 | 0.5083 | 0.7130 |
No log | 3.6 | 198 | 0.5088 | 0.5596 | 0.5088 | 0.7133 |
No log | 3.6364 | 200 | 0.6137 | 0.5528 | 0.6137 | 0.7834 |
No log | 3.6727 | 202 | 0.6838 | 0.5018 | 0.6838 | 0.8269 |
No log | 3.7091 | 204 | 0.6155 | 0.5735 | 0.6155 | 0.7846 |
No log | 3.7455 | 206 | 0.5426 | 0.5184 | 0.5426 | 0.7366 |
No log | 3.7818 | 208 | 0.5201 | 0.5677 | 0.5201 | 0.7212 |
No log | 3.8182 | 210 | 0.5297 | 0.5951 | 0.5297 | 0.7278 |
No log | 3.8545 | 212 | 0.5135 | 0.5184 | 0.5135 | 0.7166 |
No log | 3.8909 | 214 | 0.5285 | 0.5168 | 0.5285 | 0.7270 |
No log | 3.9273 | 216 | 0.5328 | 0.5250 | 0.5328 | 0.7299 |
No log | 3.9636 | 218 | 0.5161 | 0.5492 | 0.5161 | 0.7184 |
No log | 4.0 | 220 | 0.5380 | 0.4782 | 0.5380 | 0.7335 |
No log | 4.0364 | 222 | 0.5548 | 0.4847 | 0.5548 | 0.7449 |
No log | 4.0727 | 224 | 0.5401 | 0.4847 | 0.5401 | 0.7349 |
No log | 4.1091 | 226 | 0.5157 | 0.4866 | 0.5157 | 0.7181 |
No log | 4.1455 | 228 | 0.5421 | 0.4979 | 0.5421 | 0.7363 |
No log | 4.1818 | 230 | 0.5692 | 0.4756 | 0.5692 | 0.7544 |
No log | 4.2182 | 232 | 0.5332 | 0.4367 | 0.5332 | 0.7302 |
No log | 4.2545 | 234 | 0.5320 | 0.4229 | 0.5320 | 0.7294 |
No log | 4.2909 | 236 | 0.5618 | 0.4597 | 0.5618 | 0.7495 |
No log | 4.3273 | 238 | 0.5322 | 0.4660 | 0.5322 | 0.7296 |
No log | 4.3636 | 240 | 0.5036 | 0.4829 | 0.5036 | 0.7097 |
No log | 4.4 | 242 | 0.5134 | 0.4486 | 0.5134 | 0.7165 |
No log | 4.4364 | 244 | 0.5822 | 0.5384 | 0.5822 | 0.7630 |
No log | 4.4727 | 246 | 0.5779 | 0.5384 | 0.5779 | 0.7602 |
No log | 4.5091 | 248 | 0.4957 | 0.5319 | 0.4957 | 0.7041 |
No log | 4.5455 | 250 | 0.4913 | 0.5306 | 0.4913 | 0.7009 |
No log | 4.5818 | 252 | 0.5166 | 0.5501 | 0.5166 | 0.7187 |
No log | 4.6182 | 254 | 0.5761 | 0.5395 | 0.5761 | 0.7590 |
No log | 4.6545 | 256 | 0.5460 | 0.5485 | 0.5460 | 0.7389 |
No log | 4.6909 | 258 | 0.4907 | 0.4892 | 0.4907 | 0.7005 |
No log | 4.7273 | 260 | 0.5084 | 0.5649 | 0.5084 | 0.7130 |
No log | 4.7636 | 262 | 0.5325 | 0.5467 | 0.5325 | 0.7297 |
No log | 4.8 | 264 | 0.5180 | 0.5270 | 0.5180 | 0.7197 |
No log | 4.8364 | 266 | 0.5321 | 0.4958 | 0.5321 | 0.7295 |
No log | 4.8727 | 268 | 0.5429 | 0.4919 | 0.5429 | 0.7368 |
No log | 4.9091 | 270 | 0.5230 | 0.4847 | 0.5230 | 0.7232 |
No log | 4.9455 | 272 | 0.5179 | 0.4484 | 0.5179 | 0.7196 |
No log | 4.9818 | 274 | 0.5150 | 0.4484 | 0.5150 | 0.7176 |
No log | 5.0182 | 276 | 0.5149 | 0.4147 | 0.5149 | 0.7176 |
No log | 5.0545 | 278 | 0.5323 | 0.4397 | 0.5323 | 0.7296 |
No log | 5.0909 | 280 | 0.5246 | 0.4397 | 0.5246 | 0.7243 |
No log | 5.1273 | 282 | 0.4888 | 0.5089 | 0.4888 | 0.6992 |
No log | 5.1636 | 284 | 0.5065 | 0.5495 | 0.5065 | 0.7117 |
No log | 5.2 | 286 | 0.5191 | 0.5718 | 0.5191 | 0.7205 |
No log | 5.2364 | 288 | 0.5268 | 0.5970 | 0.5268 | 0.7258 |
No log | 5.2727 | 290 | 0.5484 | 0.6169 | 0.5484 | 0.7406 |
No log | 5.3091 | 292 | 0.5424 | 0.5881 | 0.5424 | 0.7365 |
No log | 5.3455 | 294 | 0.5292 | 0.5494 | 0.5292 | 0.7275 |
No log | 5.3818 | 296 | 0.5226 | 0.5336 | 0.5226 | 0.7229 |
No log | 5.4182 | 298 | 0.5213 | 0.5436 | 0.5213 | 0.7220 |
No log | 5.4545 | 300 | 0.5375 | 0.5933 | 0.5375 | 0.7331 |
No log | 5.4909 | 302 | 0.5269 | 0.5495 | 0.5269 | 0.7259 |
No log | 5.5273 | 304 | 0.5071 | 0.5125 | 0.5071 | 0.7121 |
No log | 5.5636 | 306 | 0.5345 | 0.4895 | 0.5345 | 0.7311 |
No log | 5.6 | 308 | 0.5497 | 0.4292 | 0.5497 | 0.7414 |
No log | 5.6364 | 310 | 0.5164 | 0.4953 | 0.5164 | 0.7186 |
No log | 5.6727 | 312 | 0.5375 | 0.5841 | 0.5375 | 0.7332 |
No log | 5.7091 | 314 | 0.5725 | 0.5841 | 0.5725 | 0.7566 |
No log | 5.7455 | 316 | 0.5352 | 0.5178 | 0.5352 | 0.7316 |
No log | 5.7818 | 318 | 0.5442 | 0.4895 | 0.5442 | 0.7377 |
No log | 5.8182 | 320 | 0.6327 | 0.3942 | 0.6327 | 0.7954 |
No log | 5.8545 | 322 | 0.6268 | 0.4134 | 0.6268 | 0.7917 |
No log | 5.8909 | 324 | 0.6210 | 0.4393 | 0.6210 | 0.7880 |
No log | 5.9273 | 326 | 0.5948 | 0.4377 | 0.5948 | 0.7712 |
No log | 5.9636 | 328 | 0.6060 | 0.4301 | 0.6060 | 0.7785 |
No log | 6.0 | 330 | 0.6001 | 0.3574 | 0.6001 | 0.7747 |
No log | 6.0364 | 332 | 0.6206 | 0.3665 | 0.6206 | 0.7878 |
No log | 6.0727 | 334 | 0.6051 | 0.3738 | 0.6051 | 0.7779 |
No log | 6.1091 | 336 | 0.6031 | 0.3324 | 0.6031 | 0.7766 |
No log | 6.1455 | 338 | 0.6042 | 0.3649 | 0.6042 | 0.7773 |
No log | 6.1818 | 340 | 0.5722 | 0.4052 | 0.5722 | 0.7564 |
No log | 6.2182 | 342 | 0.5466 | 0.3318 | 0.5466 | 0.7393 |
No log | 6.2545 | 344 | 0.5322 | 0.4161 | 0.5322 | 0.7296 |
No log | 6.2909 | 346 | 0.5403 | 0.4547 | 0.5403 | 0.7351 |
No log | 6.3273 | 348 | 0.5516 | 0.3840 | 0.5516 | 0.7427 |
No log | 6.3636 | 350 | 0.5302 | 0.4681 | 0.5302 | 0.7282 |
No log | 6.4 | 352 | 0.5335 | 0.4809 | 0.5335 | 0.7304 |
No log | 6.4364 | 354 | 0.5483 | 0.4782 | 0.5483 | 0.7405 |
No log | 6.4727 | 356 | 0.5560 | 0.4717 | 0.5560 | 0.7456 |
No log | 6.5091 | 358 | 0.5343 | 0.4299 | 0.5343 | 0.7309 |
No log | 6.5455 | 360 | 0.5439 | 0.4267 | 0.5439 | 0.7375 |
No log | 6.5818 | 362 | 0.5958 | 0.3763 | 0.5958 | 0.7719 |
No log | 6.6182 | 364 | 0.5778 | 0.4267 | 0.5778 | 0.7601 |
No log | 6.6545 | 366 | 0.5707 | 0.4267 | 0.5707 | 0.7554 |
No log | 6.6909 | 368 | 0.5830 | 0.4182 | 0.5830 | 0.7635 |
No log | 6.7273 | 370 | 0.5710 | 0.4267 | 0.5710 | 0.7556 |
No log | 6.7636 | 372 | 0.5622 | 0.4504 | 0.5622 | 0.7498 |
No log | 6.8 | 374 | 0.5784 | 0.4747 | 0.5784 | 0.7605 |
No log | 6.8364 | 376 | 0.5931 | 0.4747 | 0.5931 | 0.7702 |
No log | 6.8727 | 378 | 0.5996 | 0.4747 | 0.5996 | 0.7743 |
No log | 6.9091 | 380 | 0.5982 | 0.4747 | 0.5982 | 0.7735 |
No log | 6.9455 | 382 | 0.5934 | 0.4747 | 0.5934 | 0.7703 |
No log | 6.9818 | 384 | 0.5838 | 0.4747 | 0.5838 | 0.7641 |
No log | 7.0182 | 386 | 0.6028 | 0.4044 | 0.6028 | 0.7764 |
No log | 7.0545 | 388 | 0.6047 | 0.4044 | 0.6047 | 0.7776 |
No log | 7.0909 | 390 | 0.5935 | 0.4726 | 0.5935 | 0.7704 |
No log | 7.1273 | 392 | 0.6021 | 0.4044 | 0.6021 | 0.7760 |
No log | 7.1636 | 394 | 0.5872 | 0.4459 | 0.5872 | 0.7663 |
No log | 7.2 | 396 | 0.5688 | 0.4816 | 0.5688 | 0.7542 |
No log | 7.2364 | 398 | 0.5566 | 0.4816 | 0.5566 | 0.7460 |
No log | 7.2727 | 400 | 0.5631 | 0.4726 | 0.5631 | 0.7504 |
No log | 7.3091 | 402 | 0.5413 | 0.4504 | 0.5413 | 0.7357 |
No log | 7.3455 | 404 | 0.5383 | 0.4722 | 0.5383 | 0.7337 |
No log | 7.3818 | 406 | 0.5397 | 0.4885 | 0.5397 | 0.7347 |
No log | 7.4182 | 408 | 0.5435 | 0.4300 | 0.5435 | 0.7372 |
No log | 7.4545 | 410 | 0.5391 | 0.4637 | 0.5391 | 0.7342 |
No log | 7.4909 | 412 | 0.5342 | 0.4904 | 0.5342 | 0.7309 |
No log | 7.5273 | 414 | 0.5377 | 0.4942 | 0.5377 | 0.7333 |
No log | 7.5636 | 416 | 0.5285 | 0.4904 | 0.5285 | 0.7270 |
No log | 7.6 | 418 | 0.5528 | 0.4914 | 0.5528 | 0.7435 |
No log | 7.6364 | 420 | 0.5986 | 0.4393 | 0.5986 | 0.7737 |
No log | 7.6727 | 422 | 0.5712 | 0.4895 | 0.5712 | 0.7558 |
No log | 7.7091 | 424 | 0.5514 | 0.4782 | 0.5514 | 0.7426 |
No log | 7.7455 | 426 | 0.5651 | 0.4635 | 0.5651 | 0.7517 |
No log | 7.7818 | 428 | 0.6391 | 0.5051 | 0.6391 | 0.7994 |
No log | 7.8182 | 430 | 0.6897 | 0.4833 | 0.6897 | 0.8305 |
No log | 7.8545 | 432 | 0.6819 | 0.4833 | 0.6819 | 0.8258 |
No log | 7.8909 | 434 | 0.6059 | 0.4908 | 0.6059 | 0.7784 |
No log | 7.9273 | 436 | 0.5438 | 0.4345 | 0.5438 | 0.7374 |
No log | 7.9636 | 438 | 0.5395 | 0.4299 | 0.5395 | 0.7345 |
No log | 8.0 | 440 | 0.5455 | 0.3889 | 0.5455 | 0.7386 |
No log | 8.0364 | 442 | 0.5524 | 0.3920 | 0.5524 | 0.7433 |
No log | 8.0727 | 444 | 0.5629 | 0.3604 | 0.5629 | 0.7503 |
No log | 8.1091 | 446 | 0.5707 | 0.3604 | 0.5707 | 0.7555 |
No log | 8.1455 | 448 | 0.5697 | 0.3633 | 0.5697 | 0.7548 |
No log | 8.1818 | 450 | 0.5686 | 0.4161 | 0.5686 | 0.7540 |
No log | 8.2182 | 452 | 0.5713 | 0.3889 | 0.5713 | 0.7558 |
No log | 8.2545 | 454 | 0.5707 | 0.4224 | 0.5707 | 0.7555 |
No log | 8.2909 | 456 | 0.5776 | 0.4291 | 0.5776 | 0.7600 |
No log | 8.3273 | 458 | 0.5654 | 0.4752 | 0.5654 | 0.7519 |
No log | 8.3636 | 460 | 0.5629 | 0.3889 | 0.5629 | 0.7503 |
No log | 8.4 | 462 | 0.5662 | 0.3019 | 0.5662 | 0.7525 |
No log | 8.4364 | 464 | 0.5805 | 0.3781 | 0.5805 | 0.7619 |
No log | 8.4727 | 466 | 0.5883 | 0.3675 | 0.5883 | 0.7670 |
No log | 8.5091 | 468 | 0.5690 | 0.4747 | 0.5690 | 0.7543 |
No log | 8.5455 | 470 | 0.5659 | 0.4596 | 0.5659 | 0.7523 |
No log | 8.5818 | 472 | 0.5723 | 0.4681 | 0.5723 | 0.7565 |
No log | 8.6182 | 474 | 0.5603 | 0.4596 | 0.5603 | 0.7486 |
No log | 8.6545 | 476 | 0.5577 | 0.4828 | 0.5577 | 0.7468 |
No log | 8.6909 | 478 | 0.5710 | 0.4828 | 0.5710 | 0.7556 |
No log | 8.7273 | 480 | 0.6228 | 0.4448 | 0.6228 | 0.7892 |
No log | 8.7636 | 482 | 0.6272 | 0.4413 | 0.6272 | 0.7920 |
No log | 8.8 | 484 | 0.5898 | 0.4434 | 0.5898 | 0.7680 |
No log | 8.8364 | 486 | 0.5691 | 0.4828 | 0.5691 | 0.7544 |
No log | 8.8727 | 488 | 0.5543 | 0.4914 | 0.5543 | 0.7445 |
No log | 8.9091 | 490 | 0.5704 | 0.4964 | 0.5704 | 0.7553 |
No log | 8.9455 | 492 | 0.5623 | 0.5056 | 0.5623 | 0.7499 |
No log | 8.9818 | 494 | 0.5421 | 0.4276 | 0.5421 | 0.7363 |
No log | 9.0182 | 496 | 0.5439 | 0.4019 | 0.5439 | 0.7375 |
No log | 9.0545 | 498 | 0.5450 | 0.4019 | 0.5450 | 0.7382 |
0.246 | 9.0909 | 500 | 0.5568 | 0.4526 | 0.5568 | 0.7462 |
0.246 | 9.1273 | 502 | 0.6175 | 0.3737 | 0.6175 | 0.7858 |
0.246 | 9.1636 | 504 | 0.6380 | 0.3662 | 0.6380 | 0.7987 |
0.246 | 9.2 | 506 | 0.5908 | 0.4639 | 0.5908 | 0.7686 |
0.246 | 9.2364 | 508 | 0.5404 | 0.4276 | 0.5404 | 0.7351 |
0.246 | 9.2727 | 510 | 0.5684 | 0.4227 | 0.5684 | 0.7539 |
0.246 | 9.3091 | 512 | 0.5765 | 0.4227 | 0.5765 | 0.7593 |
0.246 | 9.3455 | 514 | 0.5522 | 0.3988 | 0.5522 | 0.7431 |
0.246 | 9.3818 | 516 | 0.5531 | 0.4526 | 0.5531 | 0.7437 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 5
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/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run999_AugV5_k10_task7_organization
Base model
aubmindlab/bert-base-arabertv02