Instructions to use MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k12_task3_organization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k12_task3_organization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k12_task3_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k12_task3_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k12_task3_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k12_task3_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: 1.2710
- Qwk: 0.1158
- Mse: 1.2710
- Rmse: 1.1274
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 | 0.0377 | 2 | 3.1547 | -0.0341 | 3.1547 | 1.7761 |
| No log | 0.0755 | 4 | 1.6949 | 0.0255 | 1.6949 | 1.3019 |
| No log | 0.1132 | 6 | 0.9501 | 0.0418 | 0.9501 | 0.9747 |
| No log | 0.1509 | 8 | 0.7525 | 0.1915 | 0.7525 | 0.8675 |
| No log | 0.1887 | 10 | 0.6077 | 0.0071 | 0.6077 | 0.7795 |
| No log | 0.2264 | 12 | 0.6680 | -0.0732 | 0.6680 | 0.8173 |
| No log | 0.2642 | 14 | 0.7703 | -0.2810 | 0.7703 | 0.8777 |
| No log | 0.3019 | 16 | 0.8278 | -0.0872 | 0.8278 | 0.9099 |
| No log | 0.3396 | 18 | 0.8166 | -0.0090 | 0.8166 | 0.9037 |
| No log | 0.3774 | 20 | 0.8066 | 0.0 | 0.8066 | 0.8981 |
| No log | 0.4151 | 22 | 0.8663 | -0.0081 | 0.8663 | 0.9308 |
| No log | 0.4528 | 24 | 0.7294 | 0.0952 | 0.7294 | 0.8540 |
| No log | 0.4906 | 26 | 0.6440 | 0.0 | 0.6440 | 0.8025 |
| No log | 0.5283 | 28 | 0.6910 | 0.0 | 0.6910 | 0.8313 |
| No log | 0.5660 | 30 | 0.7556 | 0.0 | 0.7556 | 0.8693 |
| No log | 0.6038 | 32 | 0.8173 | -0.0133 | 0.8173 | 0.9040 |
| No log | 0.6415 | 34 | 0.8209 | 0.0968 | 0.8209 | 0.9060 |
| No log | 0.6792 | 36 | 0.7278 | -0.0560 | 0.7278 | 0.8531 |
| No log | 0.7170 | 38 | 0.6938 | 0.0 | 0.6938 | 0.8329 |
| No log | 0.7547 | 40 | 0.6768 | 0.0 | 0.6768 | 0.8227 |
| No log | 0.7925 | 42 | 0.6617 | 0.0388 | 0.6617 | 0.8134 |
| No log | 0.8302 | 44 | 0.7603 | 0.0164 | 0.7603 | 0.8720 |
| No log | 0.8679 | 46 | 0.7921 | -0.0667 | 0.7921 | 0.8900 |
| No log | 0.9057 | 48 | 0.8032 | -0.1124 | 0.8032 | 0.8962 |
| No log | 0.9434 | 50 | 0.9225 | 0.0857 | 0.9225 | 0.9605 |
| No log | 0.9811 | 52 | 0.8314 | 0.0164 | 0.8314 | 0.9118 |
| No log | 1.0189 | 54 | 0.6775 | -0.0159 | 0.6775 | 0.8231 |
| No log | 1.0566 | 56 | 0.6855 | -0.0370 | 0.6855 | 0.8279 |
| No log | 1.0943 | 58 | 0.6740 | -0.0963 | 0.6740 | 0.8210 |
| No log | 1.1321 | 60 | 0.6462 | -0.0159 | 0.6462 | 0.8038 |
| No log | 1.1698 | 62 | 0.6364 | -0.0233 | 0.6364 | 0.7978 |
| No log | 1.2075 | 64 | 0.6558 | 0.0189 | 0.6558 | 0.8098 |
| No log | 1.2453 | 66 | 0.6592 | 0.0769 | 0.6592 | 0.8119 |
| No log | 1.2830 | 68 | 0.7955 | 0.0130 | 0.7955 | 0.8919 |
| No log | 1.3208 | 70 | 0.9065 | 0.0 | 0.9065 | 0.9521 |
| No log | 1.3585 | 72 | 0.8894 | 0.1028 | 0.8894 | 0.9431 |
| No log | 1.3962 | 74 | 0.6572 | 0.0 | 0.6572 | 0.8107 |
| No log | 1.4340 | 76 | 0.6478 | 0.2000 | 0.6478 | 0.8049 |
| No log | 1.4717 | 78 | 0.6720 | 0.1905 | 0.6720 | 0.8197 |
| No log | 1.5094 | 80 | 0.6085 | 0.1773 | 0.6085 | 0.7801 |
| No log | 1.5472 | 82 | 0.8457 | 0.1005 | 0.8457 | 0.9196 |
| No log | 1.5849 | 84 | 1.1130 | 0.0303 | 1.1130 | 1.0550 |
| No log | 1.6226 | 86 | 1.1077 | 0.0365 | 1.1077 | 1.0525 |
| No log | 1.6604 | 88 | 0.7259 | 0.1398 | 0.7259 | 0.8520 |
| No log | 1.6981 | 90 | 0.5869 | 0.1788 | 0.5869 | 0.7661 |
| No log | 1.7358 | 92 | 0.6132 | 0.2821 | 0.6132 | 0.7831 |
| No log | 1.7736 | 94 | 0.8484 | 0.1321 | 0.8484 | 0.9211 |
| No log | 1.8113 | 96 | 0.9216 | 0.0182 | 0.9216 | 0.9600 |
| No log | 1.8491 | 98 | 1.2051 | -0.0544 | 1.2051 | 1.0978 |
| No log | 1.8868 | 100 | 1.3361 | -0.0196 | 1.3361 | 1.1559 |
| No log | 1.9245 | 102 | 1.3628 | 0.0515 | 1.3628 | 1.1674 |
| No log | 1.9623 | 104 | 0.6824 | 0.1340 | 0.6824 | 0.8261 |
| No log | 2.0 | 106 | 0.6144 | 0.2418 | 0.6144 | 0.7838 |
| No log | 2.0377 | 108 | 0.6575 | 0.2707 | 0.6575 | 0.8109 |
| No log | 2.0755 | 110 | 0.7853 | 0.1712 | 0.7853 | 0.8862 |
| No log | 2.1132 | 112 | 0.8392 | 0.0847 | 0.8392 | 0.9161 |
| No log | 2.1509 | 114 | 1.0536 | 0.1062 | 1.0536 | 1.0264 |
| No log | 2.1887 | 116 | 1.1307 | 0.1212 | 1.1307 | 1.0634 |
| No log | 2.2264 | 118 | 1.1244 | 0.0861 | 1.1244 | 1.0604 |
| No log | 2.2642 | 120 | 0.9631 | 0.0979 | 0.9631 | 0.9814 |
| No log | 2.3019 | 122 | 0.6574 | 0.2542 | 0.6574 | 0.8108 |
| No log | 2.3396 | 124 | 0.6088 | 0.2000 | 0.6088 | 0.7803 |
| No log | 2.3774 | 126 | 0.6780 | 0.2432 | 0.6780 | 0.8234 |
| No log | 2.4151 | 128 | 1.2658 | 0.1233 | 1.2658 | 1.1251 |
| No log | 2.4528 | 130 | 1.4012 | 0.0657 | 1.4012 | 1.1837 |
| No log | 2.4906 | 132 | 1.1399 | -0.0450 | 1.1399 | 1.0677 |
| No log | 2.5283 | 134 | 1.0207 | -0.1148 | 1.0207 | 1.0103 |
| No log | 2.5660 | 136 | 0.9215 | -0.0950 | 0.9215 | 0.9599 |
| No log | 2.6038 | 138 | 0.8914 | -0.0053 | 0.8914 | 0.9441 |
| No log | 2.6415 | 140 | 0.8873 | 0.1034 | 0.8873 | 0.9419 |
| No log | 2.6792 | 142 | 0.9217 | 0.1486 | 0.9217 | 0.9601 |
| No log | 2.7170 | 144 | 1.0196 | 0.1235 | 1.0196 | 1.0098 |
| No log | 2.7547 | 146 | 1.0845 | 0.0958 | 1.0845 | 1.0414 |
| No log | 2.7925 | 148 | 1.0382 | 0.0598 | 1.0382 | 1.0189 |
| No log | 2.8302 | 150 | 1.2112 | 0.0614 | 1.2112 | 1.1005 |
| No log | 2.8679 | 152 | 1.4083 | 0.12 | 1.4083 | 1.1867 |
| No log | 2.9057 | 154 | 1.4399 | 0.12 | 1.4399 | 1.1999 |
| No log | 2.9434 | 156 | 1.3068 | 0.1186 | 1.3068 | 1.1432 |
| No log | 2.9811 | 158 | 1.1934 | 0.0556 | 1.1934 | 1.0924 |
| No log | 3.0189 | 160 | 1.2643 | 0.0210 | 1.2643 | 1.1244 |
| No log | 3.0566 | 162 | 1.4254 | 0.1141 | 1.4254 | 1.1939 |
| No log | 3.0943 | 164 | 1.3009 | 0.1126 | 1.3009 | 1.1406 |
| No log | 3.1321 | 166 | 0.9007 | 0.1493 | 0.9007 | 0.9490 |
| No log | 3.1698 | 168 | 0.8218 | 0.2609 | 0.8218 | 0.9065 |
| No log | 3.2075 | 170 | 1.0723 | 0.0888 | 1.0723 | 1.0355 |
| No log | 3.2453 | 172 | 1.6979 | 0.1254 | 1.6979 | 1.3030 |
| No log | 3.2830 | 174 | 2.2839 | 0.0195 | 2.2839 | 1.5112 |
| No log | 3.3208 | 176 | 2.1012 | 0.0485 | 2.1012 | 1.4495 |
| No log | 3.3585 | 178 | 1.6974 | 0.0960 | 1.6974 | 1.3029 |
| No log | 3.3962 | 180 | 1.2166 | 0.0657 | 1.2166 | 1.1030 |
| No log | 3.4340 | 182 | 0.8989 | 0.1228 | 0.8989 | 0.9481 |
| No log | 3.4717 | 184 | 0.9223 | 0.1304 | 0.9223 | 0.9604 |
| No log | 3.5094 | 186 | 1.4498 | 0.1342 | 1.4498 | 1.2041 |
| No log | 3.5472 | 188 | 1.7455 | 0.1342 | 1.7455 | 1.3212 |
| No log | 3.5849 | 190 | 1.3520 | 0.1354 | 1.3520 | 1.1627 |
| No log | 3.6226 | 192 | 1.1136 | 0.0949 | 1.1136 | 1.0553 |
| No log | 3.6604 | 194 | 1.1894 | 0.1176 | 1.1894 | 1.0906 |
| No log | 3.6981 | 196 | 1.2617 | 0.0463 | 1.2617 | 1.1233 |
| No log | 3.7358 | 198 | 1.4426 | 0.0033 | 1.4426 | 1.2011 |
| No log | 3.7736 | 200 | 1.6690 | 0.0127 | 1.6690 | 1.2919 |
| No log | 3.8113 | 202 | 1.7160 | 0.0508 | 1.7160 | 1.3100 |
| No log | 3.8491 | 204 | 1.5262 | 0.0695 | 1.5262 | 1.2354 |
| No log | 3.8868 | 206 | 1.2682 | 0.0941 | 1.2682 | 1.1261 |
| No log | 3.9245 | 208 | 1.0869 | 0.0579 | 1.0869 | 1.0425 |
| No log | 3.9623 | 210 | 1.1219 | 0.0406 | 1.1219 | 1.0592 |
| No log | 4.0 | 212 | 1.5144 | 0.1354 | 1.5144 | 1.2306 |
| No log | 4.0377 | 214 | 1.6487 | 0.1136 | 1.6487 | 1.2840 |
| No log | 4.0755 | 216 | 1.2283 | 0.1241 | 1.2283 | 1.1083 |
| No log | 4.1132 | 218 | 1.0041 | 0.0588 | 1.0041 | 1.0021 |
| No log | 4.1509 | 220 | 0.9374 | 0.1169 | 0.9374 | 0.9682 |
| No log | 4.1887 | 222 | 0.9090 | 0.0933 | 0.9090 | 0.9534 |
| No log | 4.2264 | 224 | 0.9983 | 0.0569 | 0.9983 | 0.9992 |
| No log | 4.2642 | 226 | 1.3286 | 0.1293 | 1.3286 | 1.1527 |
| No log | 4.3019 | 228 | 1.5814 | 0.0946 | 1.5814 | 1.2575 |
| No log | 4.3396 | 230 | 1.3631 | 0.1070 | 1.3631 | 1.1675 |
| No log | 4.3774 | 232 | 0.9313 | 0.0744 | 0.9313 | 0.9650 |
| No log | 4.4151 | 234 | 0.7622 | 0.1917 | 0.7622 | 0.8730 |
| No log | 4.4528 | 236 | 0.7721 | 0.2000 | 0.7721 | 0.8787 |
| No log | 4.4906 | 238 | 0.8437 | 0.0385 | 0.8437 | 0.9185 |
| No log | 4.5283 | 240 | 1.2248 | 0.1037 | 1.2248 | 1.1067 |
| No log | 4.5660 | 242 | 1.6246 | 0.0386 | 1.6246 | 1.2746 |
| No log | 4.6038 | 244 | 1.8186 | 0.0444 | 1.8186 | 1.3486 |
| No log | 4.6415 | 246 | 1.5920 | -0.0123 | 1.5920 | 1.2617 |
| No log | 4.6792 | 248 | 1.3143 | -0.0780 | 1.3143 | 1.1464 |
| No log | 4.7170 | 250 | 1.1556 | 0.0445 | 1.1556 | 1.0750 |
| No log | 4.7547 | 252 | 1.1348 | 0.1176 | 1.1348 | 1.0653 |
| No log | 4.7925 | 254 | 1.1936 | 0.0769 | 1.1936 | 1.0925 |
| No log | 4.8302 | 256 | 1.4291 | 0.0952 | 1.4291 | 1.1955 |
| No log | 4.8679 | 258 | 1.5143 | 0.0968 | 1.5143 | 1.2306 |
| No log | 4.9057 | 260 | 1.2984 | 0.1182 | 1.2984 | 1.1395 |
| No log | 4.9434 | 262 | 0.9548 | 0.0866 | 0.9548 | 0.9771 |
| No log | 4.9811 | 264 | 0.8855 | 0.0979 | 0.8855 | 0.9410 |
| No log | 5.0189 | 266 | 1.0220 | 0.1486 | 1.0220 | 1.0109 |
| No log | 5.0566 | 268 | 1.2427 | 0.0704 | 1.2427 | 1.1148 |
| No log | 5.0943 | 270 | 1.4466 | 0.0299 | 1.4466 | 1.2027 |
| No log | 5.1321 | 272 | 1.5671 | -0.0123 | 1.5671 | 1.2518 |
| No log | 5.1698 | 274 | 1.6361 | -0.0435 | 1.6361 | 1.2791 |
| No log | 5.2075 | 276 | 1.3837 | 0.0614 | 1.3837 | 1.1763 |
| No log | 5.2453 | 278 | 1.2739 | 0.0977 | 1.2739 | 1.1287 |
| No log | 5.2830 | 280 | 1.2388 | 0.1014 | 1.2388 | 1.1130 |
| No log | 5.3208 | 282 | 1.1315 | 0.1045 | 1.1315 | 1.0637 |
| No log | 5.3585 | 284 | 1.1421 | 0.1128 | 1.1421 | 1.0687 |
| No log | 5.3962 | 286 | 1.2773 | 0.1176 | 1.2773 | 1.1302 |
| No log | 5.4340 | 288 | 1.4597 | -0.0104 | 1.4597 | 1.2082 |
| No log | 5.4717 | 290 | 1.4208 | 0.0489 | 1.4208 | 1.1920 |
| No log | 5.5094 | 292 | 1.1557 | 0.1450 | 1.1557 | 1.0750 |
| No log | 5.5472 | 294 | 1.0615 | 0.0871 | 1.0615 | 1.0303 |
| No log | 5.5849 | 296 | 1.1932 | 0.1642 | 1.1932 | 1.0923 |
| No log | 5.6226 | 298 | 1.3015 | 0.1515 | 1.3015 | 1.1408 |
| No log | 5.6604 | 300 | 1.5415 | 0.0909 | 1.5415 | 1.2416 |
| No log | 5.6981 | 302 | 1.6269 | 0.0500 | 1.6269 | 1.2755 |
| No log | 5.7358 | 304 | 1.4693 | 0.0927 | 1.4693 | 1.2121 |
| No log | 5.7736 | 306 | 1.3881 | 0.0909 | 1.3881 | 1.1782 |
| No log | 5.8113 | 308 | 1.2157 | 0.1429 | 1.2157 | 1.1026 |
| No log | 5.8491 | 310 | 0.9947 | 0.0345 | 0.9947 | 0.9973 |
| No log | 5.8868 | 312 | 0.9874 | 0.0717 | 0.9874 | 0.9937 |
| No log | 5.9245 | 314 | 1.0925 | 0.1111 | 1.0925 | 1.0452 |
| No log | 5.9623 | 316 | 1.2036 | 0.1418 | 1.2036 | 1.0971 |
| No log | 6.0 | 318 | 1.3276 | 0.1220 | 1.3276 | 1.1522 |
| No log | 6.0377 | 320 | 1.2126 | 0.1429 | 1.2126 | 1.1012 |
| No log | 6.0755 | 322 | 1.2034 | 0.1471 | 1.2034 | 1.0970 |
| No log | 6.1132 | 324 | 1.1302 | 0.1407 | 1.1302 | 1.0631 |
| No log | 6.1509 | 326 | 1.0455 | 0.1396 | 1.0455 | 1.0225 |
| No log | 6.1887 | 328 | 0.9534 | 0.1000 | 0.9534 | 0.9764 |
| No log | 6.2264 | 330 | 0.9804 | 0.1093 | 0.9804 | 0.9902 |
| No log | 6.2642 | 332 | 1.1755 | 0.1241 | 1.1755 | 1.0842 |
| No log | 6.3019 | 334 | 1.2644 | 0.1538 | 1.2644 | 1.1244 |
| No log | 6.3396 | 336 | 1.3038 | 0.1538 | 1.3038 | 1.1419 |
| No log | 6.3774 | 338 | 1.2388 | 0.1531 | 1.2388 | 1.1130 |
| No log | 6.4151 | 340 | 1.0566 | 0.1396 | 1.0566 | 1.0279 |
| No log | 6.4528 | 342 | 1.0412 | 0.1343 | 1.0412 | 1.0204 |
| No log | 6.4906 | 344 | 1.2143 | 0.1507 | 1.2143 | 1.1020 |
| No log | 6.5283 | 346 | 1.5240 | 0.0877 | 1.5240 | 1.2345 |
| No log | 6.5660 | 348 | 1.7509 | 0.0700 | 1.7509 | 1.3232 |
| No log | 6.6038 | 350 | 1.6930 | 0.0700 | 1.6930 | 1.3012 |
| No log | 6.6415 | 352 | 1.3930 | 0.1538 | 1.3930 | 1.1802 |
| No log | 6.6792 | 354 | 1.2301 | 0.1409 | 1.2301 | 1.1091 |
| No log | 6.7170 | 356 | 1.1892 | 0.1158 | 1.1892 | 1.0905 |
| No log | 6.7547 | 358 | 1.3369 | 0.1206 | 1.3369 | 1.1562 |
| No log | 6.7925 | 360 | 1.4459 | 0.0489 | 1.4459 | 1.2025 |
| No log | 6.8302 | 362 | 1.5062 | 0.0256 | 1.5062 | 1.2273 |
| No log | 6.8679 | 364 | 1.4929 | -0.0153 | 1.4929 | 1.2218 |
| No log | 6.9057 | 366 | 1.3922 | 0.0728 | 1.3922 | 1.1799 |
| No log | 6.9434 | 368 | 1.3217 | 0.0949 | 1.3217 | 1.1496 |
| No log | 6.9811 | 370 | 1.3234 | 0.0949 | 1.3234 | 1.1504 |
| No log | 7.0189 | 372 | 1.2989 | 0.0949 | 1.2989 | 1.1397 |
| No log | 7.0566 | 374 | 1.2989 | 0.1533 | 1.2989 | 1.1397 |
| No log | 7.0943 | 376 | 1.4557 | 0.1270 | 1.4557 | 1.2065 |
| No log | 7.1321 | 378 | 1.5474 | 0.1070 | 1.5474 | 1.2440 |
| No log | 7.1698 | 380 | 1.4884 | 0.0993 | 1.4884 | 1.2200 |
| No log | 7.2075 | 382 | 1.3992 | 0.1507 | 1.3992 | 1.1829 |
| No log | 7.2453 | 384 | 1.2808 | 0.1176 | 1.2808 | 1.1317 |
| No log | 7.2830 | 386 | 1.2428 | 0.1176 | 1.2428 | 1.1148 |
| No log | 7.3208 | 388 | 1.1884 | 0.1145 | 1.1884 | 1.0902 |
| No log | 7.3585 | 390 | 1.2279 | 0.1161 | 1.2279 | 1.1081 |
| No log | 7.3962 | 392 | 1.2871 | 0.0929 | 1.2871 | 1.1345 |
| No log | 7.4340 | 394 | 1.3840 | 0.1233 | 1.3840 | 1.1764 |
| No log | 7.4717 | 396 | 1.4481 | 0.0228 | 1.4481 | 1.2034 |
| No log | 7.5094 | 398 | 1.4546 | 0.0 | 1.4546 | 1.2061 |
| No log | 7.5472 | 400 | 1.4724 | -0.0221 | 1.4724 | 1.2134 |
| No log | 7.5849 | 402 | 1.4023 | 0.0707 | 1.4023 | 1.1842 |
| No log | 7.6226 | 404 | 1.2719 | 0.0929 | 1.2719 | 1.1278 |
| No log | 7.6604 | 406 | 1.1263 | 0.1212 | 1.1263 | 1.0613 |
| No log | 7.6981 | 408 | 0.9870 | 0.1111 | 0.9870 | 0.9935 |
| No log | 7.7358 | 410 | 0.9596 | 0.0769 | 0.9596 | 0.9796 |
| No log | 7.7736 | 412 | 1.0026 | 0.1111 | 1.0026 | 1.0013 |
| No log | 7.8113 | 414 | 1.0971 | 0.1212 | 1.0971 | 1.0474 |
| No log | 7.8491 | 416 | 1.2176 | 0.0657 | 1.2176 | 1.1035 |
| No log | 7.8868 | 418 | 1.2399 | 0.0657 | 1.2399 | 1.1135 |
| No log | 7.9245 | 420 | 1.2215 | 0.0929 | 1.2215 | 1.1052 |
| No log | 7.9623 | 422 | 1.2222 | 0.0929 | 1.2222 | 1.1055 |
| No log | 8.0 | 424 | 1.2730 | 0.1206 | 1.2730 | 1.1283 |
| No log | 8.0377 | 426 | 1.3305 | 0.0941 | 1.3305 | 1.1535 |
| No log | 8.0755 | 428 | 1.4039 | 0.0959 | 1.4039 | 1.1849 |
| No log | 8.1132 | 430 | 1.3641 | 0.0941 | 1.3641 | 1.1680 |
| No log | 8.1509 | 432 | 1.3329 | 0.1206 | 1.3329 | 1.1545 |
| No log | 8.1887 | 434 | 1.2890 | 0.1158 | 1.2890 | 1.1353 |
| No log | 8.2264 | 436 | 1.3208 | 0.1220 | 1.3208 | 1.1493 |
| No log | 8.2642 | 438 | 1.3186 | 0.1220 | 1.3186 | 1.1483 |
| No log | 8.3019 | 440 | 1.3865 | 0.1053 | 1.3865 | 1.1775 |
| No log | 8.3396 | 442 | 1.4301 | 0.1097 | 1.4301 | 1.1959 |
| No log | 8.3774 | 444 | 1.4319 | 0.1097 | 1.4319 | 1.1966 |
| No log | 8.4151 | 446 | 1.4153 | 0.1083 | 1.4153 | 1.1896 |
| No log | 8.4528 | 448 | 1.3463 | 0.1304 | 1.3463 | 1.1603 |
| No log | 8.4906 | 450 | 1.3255 | 0.1220 | 1.3255 | 1.1513 |
| No log | 8.5283 | 452 | 1.3324 | 0.1220 | 1.3324 | 1.1543 |
| No log | 8.5660 | 454 | 1.3022 | 0.1158 | 1.3022 | 1.1412 |
| No log | 8.6038 | 456 | 1.3240 | 0.1158 | 1.3240 | 1.1507 |
| No log | 8.6415 | 458 | 1.3808 | 0.1206 | 1.3808 | 1.1751 |
| No log | 8.6792 | 460 | 1.4496 | 0.0959 | 1.4496 | 1.2040 |
| No log | 8.7170 | 462 | 1.5227 | 0.0489 | 1.5227 | 1.2340 |
| No log | 8.7547 | 464 | 1.5419 | 0.0513 | 1.5419 | 1.2417 |
| No log | 8.7925 | 466 | 1.4763 | 0.0489 | 1.4763 | 1.2150 |
| No log | 8.8302 | 468 | 1.3792 | 0.0941 | 1.3792 | 1.1744 |
| No log | 8.8679 | 470 | 1.3350 | 0.1158 | 1.3350 | 1.1554 |
| No log | 8.9057 | 472 | 1.2974 | 0.1158 | 1.2974 | 1.1390 |
| No log | 8.9434 | 474 | 1.2584 | 0.1158 | 1.2584 | 1.1218 |
| No log | 8.9811 | 476 | 1.2442 | 0.0882 | 1.2442 | 1.1154 |
| No log | 9.0189 | 478 | 1.2445 | 0.0882 | 1.2445 | 1.1156 |
| No log | 9.0566 | 480 | 1.2317 | 0.0882 | 1.2317 | 1.1098 |
| No log | 9.0943 | 482 | 1.2577 | 0.0903 | 1.2577 | 1.1215 |
| No log | 9.1321 | 484 | 1.3202 | 0.1270 | 1.3202 | 1.1490 |
| No log | 9.1698 | 486 | 1.3549 | 0.0809 | 1.3549 | 1.1640 |
| No log | 9.2075 | 488 | 1.3492 | 0.0809 | 1.3492 | 1.1615 |
| No log | 9.2453 | 490 | 1.3182 | 0.0789 | 1.3182 | 1.1481 |
| No log | 9.2830 | 492 | 1.3148 | 0.0789 | 1.3148 | 1.1467 |
| No log | 9.3208 | 494 | 1.3009 | 0.1507 | 1.3009 | 1.1406 |
| No log | 9.3585 | 496 | 1.2646 | 0.1172 | 1.2646 | 1.1245 |
| No log | 9.3962 | 498 | 1.2357 | 0.0882 | 1.2357 | 1.1116 |
| 0.5088 | 9.4340 | 500 | 1.2258 | 0.0882 | 1.2258 | 1.1072 |
| 0.5088 | 9.4717 | 502 | 1.2257 | 0.0882 | 1.2257 | 1.1071 |
| 0.5088 | 9.5094 | 504 | 1.2345 | 0.0882 | 1.2345 | 1.1111 |
| 0.5088 | 9.5472 | 506 | 1.2498 | 0.0882 | 1.2498 | 1.1179 |
| 0.5088 | 9.5849 | 508 | 1.2774 | 0.1158 | 1.2774 | 1.1302 |
| 0.5088 | 9.6226 | 510 | 1.2958 | 0.1158 | 1.2958 | 1.1383 |
| 0.5088 | 9.6604 | 512 | 1.3213 | 0.1206 | 1.3213 | 1.1495 |
| 0.5088 | 9.6981 | 514 | 1.3302 | 0.1206 | 1.3302 | 1.1534 |
| 0.5088 | 9.7358 | 516 | 1.3265 | 0.1206 | 1.3265 | 1.1517 |
| 0.5088 | 9.7736 | 518 | 1.3185 | 0.1206 | 1.3185 | 1.1483 |
| 0.5088 | 9.8113 | 520 | 1.3135 | 0.1206 | 1.3135 | 1.1461 |
| 0.5088 | 9.8491 | 522 | 1.3075 | 0.1206 | 1.3075 | 1.1434 |
| 0.5088 | 9.8868 | 524 | 1.2953 | 0.1158 | 1.2953 | 1.1381 |
| 0.5088 | 9.9245 | 526 | 1.2829 | 0.1158 | 1.2829 | 1.1327 |
| 0.5088 | 9.9623 | 528 | 1.2743 | 0.1158 | 1.2743 | 1.1288 |
| 0.5088 | 10.0 | 530 | 1.2710 | 0.1158 | 1.2710 | 1.1274 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
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Model tree for MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k12_task3_organization
Base model
aubmindlab/bert-base-arabertv02