Instructions to use MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_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_run3_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_run3_AugV5_k12_task3_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k12_task3_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k12_task3_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_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: 1.2680
- Qwk: 0.0882
- Mse: 1.2680
- Rmse: 1.1260
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 | 0.8172 | -0.0133 | 0.8172 | 0.9040 |
| No log | 0.6415 | 34 | 0.8208 | 0.0968 | 0.8208 | 0.9060 |
| No log | 0.6792 | 36 | 0.7277 | -0.0560 | 0.7277 | 0.8531 |
| No log | 0.7170 | 38 | 0.6938 | 0.0 | 0.6938 | 0.8330 |
| No log | 0.7547 | 40 | 0.6769 | 0.0 | 0.6769 | 0.8227 |
| No log | 0.7925 | 42 | 0.6617 | 0.0388 | 0.6617 | 0.8135 |
| No log | 0.8302 | 44 | 0.7604 | 0.0164 | 0.7604 | 0.8720 |
| No log | 0.8679 | 46 | 0.7922 | -0.0667 | 0.7922 | 0.8901 |
| No log | 0.9057 | 48 | 0.8031 | -0.1124 | 0.8031 | 0.8961 |
| No log | 0.9434 | 50 | 0.9223 | 0.0857 | 0.9223 | 0.9603 |
| No log | 0.9811 | 52 | 0.8312 | 0.0164 | 0.8312 | 0.9117 |
| No log | 1.0189 | 54 | 0.6774 | -0.0159 | 0.6774 | 0.8231 |
| No log | 1.0566 | 56 | 0.6852 | -0.0370 | 0.6852 | 0.8278 |
| No log | 1.0943 | 58 | 0.6738 | -0.0963 | 0.6738 | 0.8208 |
| No log | 1.1321 | 60 | 0.6461 | -0.0159 | 0.6461 | 0.8038 |
| No log | 1.1698 | 62 | 0.6366 | -0.0233 | 0.6366 | 0.7979 |
| No log | 1.2075 | 64 | 0.6562 | 0.0189 | 0.6562 | 0.8101 |
| No log | 1.2453 | 66 | 0.6594 | 0.0769 | 0.6594 | 0.8121 |
| No log | 1.2830 | 68 | 0.7955 | 0.0130 | 0.7955 | 0.8919 |
| No log | 1.3208 | 70 | 0.9064 | 0.0 | 0.9064 | 0.9521 |
| No log | 1.3585 | 72 | 0.8894 | 0.1028 | 0.8894 | 0.9431 |
| No log | 1.3962 | 74 | 0.6570 | 0.0 | 0.6570 | 0.8105 |
| No log | 1.4340 | 76 | 0.6481 | 0.2000 | 0.6481 | 0.8050 |
| No log | 1.4717 | 78 | 0.6722 | 0.2281 | 0.6722 | 0.8199 |
| No log | 1.5094 | 80 | 0.6086 | 0.1773 | 0.6086 | 0.7801 |
| No log | 1.5472 | 82 | 0.8465 | 0.1005 | 0.8465 | 0.9201 |
| No log | 1.5849 | 84 | 1.1139 | 0.0303 | 1.1139 | 1.0554 |
| No log | 1.6226 | 86 | 1.1081 | 0.0365 | 1.1081 | 1.0527 |
| No log | 1.6604 | 88 | 0.7256 | 0.1398 | 0.7256 | 0.8518 |
| No log | 1.6981 | 90 | 0.5865 | 0.1788 | 0.5865 | 0.7659 |
| No log | 1.7358 | 92 | 0.6137 | 0.2821 | 0.6137 | 0.7834 |
| No log | 1.7736 | 94 | 0.8498 | 0.1321 | 0.8498 | 0.9219 |
| No log | 1.8113 | 96 | 0.9222 | 0.0140 | 0.9222 | 0.9603 |
| No log | 1.8491 | 98 | 1.2026 | -0.0544 | 1.2026 | 1.0966 |
| No log | 1.8868 | 100 | 1.3320 | -0.0196 | 1.3320 | 1.1541 |
| No log | 1.9245 | 102 | 1.3542 | 0.0515 | 1.3542 | 1.1637 |
| No log | 1.9623 | 104 | 0.6769 | 0.1323 | 0.6769 | 0.8227 |
| No log | 2.0 | 106 | 0.6125 | 0.2418 | 0.6125 | 0.7826 |
| No log | 2.0377 | 108 | 0.6577 | 0.2707 | 0.6577 | 0.8110 |
| No log | 2.0755 | 110 | 0.7800 | 0.1005 | 0.7800 | 0.8832 |
| No log | 2.1132 | 112 | 0.8353 | 0.0476 | 0.8353 | 0.9140 |
| No log | 2.1509 | 114 | 1.0536 | 0.0769 | 1.0536 | 1.0265 |
| No log | 2.1887 | 116 | 1.1383 | 0.1161 | 1.1383 | 1.0669 |
| No log | 2.2264 | 118 | 1.1362 | 0.0861 | 1.1362 | 1.0659 |
| No log | 2.2642 | 120 | 0.9673 | 0.0694 | 0.9673 | 0.9835 |
| No log | 2.3019 | 122 | 0.6648 | 0.2542 | 0.6648 | 0.8154 |
| No log | 2.3396 | 124 | 0.6160 | 0.2542 | 0.6160 | 0.7848 |
| No log | 2.3774 | 126 | 0.6936 | 0.2432 | 0.6936 | 0.8328 |
| No log | 2.4151 | 128 | 1.2914 | 0.1280 | 1.2914 | 1.1364 |
| No log | 2.4528 | 130 | 1.4135 | 0.0657 | 1.4135 | 1.1889 |
| No log | 2.4906 | 132 | 1.1422 | -0.0876 | 1.1422 | 1.0687 |
| No log | 2.5283 | 134 | 1.0289 | -0.1099 | 1.0289 | 1.0143 |
| No log | 2.5660 | 136 | 0.9300 | -0.0950 | 0.9300 | 0.9644 |
| No log | 2.6038 | 138 | 0.9001 | -0.0053 | 0.9001 | 0.9487 |
| No log | 2.6415 | 140 | 0.8904 | 0.1034 | 0.8904 | 0.9436 |
| No log | 2.6792 | 142 | 0.9328 | 0.0916 | 0.9328 | 0.9658 |
| No log | 2.7170 | 144 | 1.0226 | 0.1235 | 1.0226 | 1.0112 |
| No log | 2.7547 | 146 | 1.0906 | 0.0938 | 1.0906 | 1.0443 |
| No log | 2.7925 | 148 | 1.0437 | 0.0598 | 1.0437 | 1.0216 |
| No log | 2.8302 | 150 | 1.2094 | 0.0657 | 1.2094 | 1.0997 |
| No log | 2.8679 | 152 | 1.3966 | 0.12 | 1.3966 | 1.1818 |
| No log | 2.9057 | 154 | 1.4159 | 0.0897 | 1.4159 | 1.1899 |
| No log | 2.9434 | 156 | 1.2792 | 0.0897 | 1.2792 | 1.1310 |
| No log | 2.9811 | 158 | 1.1816 | 0.0530 | 1.1816 | 1.0870 |
| No log | 3.0189 | 160 | 1.2751 | 0.0210 | 1.2751 | 1.1292 |
| No log | 3.0566 | 162 | 1.4589 | 0.1141 | 1.4589 | 1.2079 |
| No log | 3.0943 | 164 | 1.2903 | 0.0857 | 1.2903 | 1.1359 |
| No log | 3.1321 | 166 | 0.8791 | 0.2150 | 0.8791 | 0.9376 |
| No log | 3.1698 | 168 | 0.8182 | 0.2609 | 0.8182 | 0.9046 |
| No log | 3.2075 | 170 | 1.0831 | 0.0888 | 1.0831 | 1.0407 |
| No log | 3.2453 | 172 | 1.7016 | 0.1254 | 1.7016 | 1.3045 |
| No log | 3.2830 | 174 | 2.3164 | 0.0179 | 2.3164 | 1.5220 |
| No log | 3.3208 | 176 | 2.1711 | 0.0485 | 2.1711 | 1.4735 |
| No log | 3.3585 | 178 | 1.7584 | 0.1214 | 1.7584 | 1.3261 |
| No log | 3.3962 | 180 | 1.1966 | 0.0929 | 1.1966 | 1.0939 |
| No log | 3.4340 | 182 | 0.8786 | 0.1493 | 0.8786 | 0.9373 |
| No log | 3.4717 | 184 | 0.8831 | 0.1304 | 0.8831 | 0.9398 |
| No log | 3.5094 | 186 | 1.3436 | 0.1335 | 1.3436 | 1.1591 |
| No log | 3.5472 | 188 | 1.6565 | 0.1342 | 1.6565 | 1.2871 |
| No log | 3.5849 | 190 | 1.3206 | 0.1354 | 1.3206 | 1.1492 |
| No log | 3.6226 | 192 | 1.1266 | 0.1246 | 1.1266 | 1.0614 |
| No log | 3.6604 | 194 | 1.2260 | 0.0922 | 1.2260 | 1.1073 |
| No log | 3.6981 | 196 | 1.2825 | 0.0102 | 1.2825 | 1.1325 |
| No log | 3.7358 | 198 | 1.4468 | -0.0263 | 1.4468 | 1.2028 |
| No log | 3.7736 | 200 | 1.6470 | -0.0215 | 1.6470 | 1.2834 |
| No log | 3.8113 | 202 | 1.7022 | 0.0508 | 1.7022 | 1.3047 |
| No log | 3.8491 | 204 | 1.5550 | 0.0714 | 1.5550 | 1.2470 |
| No log | 3.8868 | 206 | 1.3274 | 0.1226 | 1.3274 | 1.1521 |
| No log | 3.9245 | 208 | 1.0654 | 0.0506 | 1.0654 | 1.0322 |
| No log | 3.9623 | 210 | 1.0789 | 0.0745 | 1.0789 | 1.0387 |
| No log | 4.0 | 212 | 1.5010 | 0.1354 | 1.5010 | 1.2251 |
| No log | 4.0377 | 214 | 1.6784 | 0.1342 | 1.6784 | 1.2955 |
| No log | 4.0755 | 216 | 1.2619 | 0.1498 | 1.2619 | 1.1234 |
| No log | 4.1132 | 218 | 0.9977 | 0.0588 | 0.9977 | 0.9989 |
| No log | 4.1509 | 220 | 0.9028 | 0.1493 | 0.9028 | 0.9501 |
| No log | 4.1887 | 222 | 0.8795 | 0.1174 | 0.8795 | 0.9378 |
| No log | 4.2264 | 224 | 0.9963 | 0.0522 | 0.9963 | 0.9982 |
| No log | 4.2642 | 226 | 1.3550 | 0.1056 | 1.3550 | 1.1640 |
| No log | 4.3019 | 228 | 1.6012 | 0.0663 | 1.6012 | 1.2654 |
| No log | 4.3396 | 230 | 1.3753 | 0.0807 | 1.3753 | 1.1727 |
| No log | 4.3774 | 232 | 0.9410 | 0.0308 | 0.9410 | 0.9701 |
| No log | 4.4151 | 234 | 0.7814 | 0.2000 | 0.7814 | 0.8840 |
| No log | 4.4528 | 236 | 0.7919 | 0.2000 | 0.7919 | 0.8899 |
| No log | 4.4906 | 238 | 0.8662 | 0.0685 | 0.8662 | 0.9307 |
| No log | 4.5283 | 240 | 1.2422 | 0.1475 | 1.2422 | 1.1146 |
| No log | 4.5660 | 242 | 1.6357 | -0.0029 | 1.6357 | 1.2789 |
| No log | 4.6038 | 244 | 1.8397 | 0.0685 | 1.8397 | 1.3564 |
| No log | 4.6415 | 246 | 1.6163 | 0.0171 | 1.6163 | 1.2714 |
| No log | 4.6792 | 248 | 1.3061 | 0.0922 | 1.3061 | 1.1429 |
| No log | 4.7170 | 250 | 1.0944 | 0.0445 | 1.0944 | 1.0462 |
| No log | 4.7547 | 252 | 1.0446 | 0.1161 | 1.0446 | 1.0221 |
| No log | 4.7925 | 254 | 1.1677 | 0.0769 | 1.1677 | 1.0806 |
| No log | 4.8302 | 256 | 1.4764 | 0.0952 | 1.4764 | 1.2151 |
| No log | 4.8679 | 258 | 1.5915 | 0.0270 | 1.5915 | 1.2615 |
| No log | 4.9057 | 260 | 1.3728 | 0.0440 | 1.3728 | 1.1717 |
| No log | 4.9434 | 262 | 0.9758 | 0.1264 | 0.9758 | 0.9878 |
| No log | 4.9811 | 264 | 0.7997 | 0.1619 | 0.7997 | 0.8942 |
| No log | 5.0189 | 266 | 0.8467 | 0.1273 | 0.8467 | 0.9202 |
| No log | 5.0566 | 268 | 1.0315 | 0.1197 | 1.0315 | 1.0156 |
| No log | 5.0943 | 270 | 1.3538 | 0.0299 | 1.3538 | 1.1635 |
| No log | 5.1321 | 272 | 1.6075 | 0.0180 | 1.6075 | 1.2679 |
| No log | 5.1698 | 274 | 1.7044 | -0.0642 | 1.7044 | 1.3055 |
| No log | 5.2075 | 276 | 1.4384 | 0.0173 | 1.4384 | 1.1993 |
| No log | 5.2453 | 278 | 1.2924 | 0.0662 | 1.2924 | 1.1369 |
| No log | 5.2830 | 280 | 1.2305 | 0.0922 | 1.2305 | 1.1093 |
| No log | 5.3208 | 282 | 1.1108 | 0.0949 | 1.1108 | 1.0539 |
| No log | 5.3585 | 284 | 1.1159 | 0.1343 | 1.1159 | 1.0564 |
| No log | 5.3962 | 286 | 1.2653 | 0.1176 | 1.2653 | 1.1249 |
| No log | 5.4340 | 288 | 1.4240 | 0.0423 | 1.4240 | 1.1933 |
| No log | 5.4717 | 290 | 1.3553 | 0.0423 | 1.3553 | 1.1642 |
| No log | 5.5094 | 292 | 1.0970 | 0.1254 | 1.0970 | 1.0474 |
| No log | 5.5472 | 294 | 1.0050 | 0.0445 | 1.0050 | 1.0025 |
| No log | 5.5849 | 296 | 1.1081 | 0.1176 | 1.1081 | 1.0527 |
| No log | 5.6226 | 298 | 1.2285 | 0.1280 | 1.2285 | 1.1084 |
| No log | 5.6604 | 300 | 1.4993 | 0.1169 | 1.4993 | 1.2244 |
| No log | 5.6981 | 302 | 1.5918 | 0.0968 | 1.5918 | 1.2617 |
| No log | 5.7358 | 304 | 1.4307 | 0.1213 | 1.4307 | 1.1961 |
| No log | 5.7736 | 306 | 1.3487 | 0.12 | 1.3487 | 1.1613 |
| No log | 5.8113 | 308 | 1.1536 | 0.1128 | 1.1536 | 1.0740 |
| No log | 5.8491 | 310 | 0.9337 | 0.0545 | 0.9337 | 0.9663 |
| No log | 5.8868 | 312 | 0.9224 | 0.0852 | 0.9224 | 0.9604 |
| No log | 5.9245 | 314 | 1.0235 | 0.1093 | 1.0235 | 1.0117 |
| No log | 5.9623 | 316 | 1.1765 | 0.1145 | 1.1765 | 1.0847 |
| No log | 6.0 | 318 | 1.3089 | 0.1220 | 1.3089 | 1.1441 |
| No log | 6.0377 | 320 | 1.2237 | 0.1191 | 1.2237 | 1.1062 |
| No log | 6.0755 | 322 | 1.2208 | 0.1191 | 1.2208 | 1.1049 |
| No log | 6.1132 | 324 | 1.1485 | 0.1407 | 1.1485 | 1.0717 |
| No log | 6.1509 | 326 | 1.0306 | 0.1396 | 1.0306 | 1.0152 |
| No log | 6.1887 | 328 | 0.8981 | 0.1261 | 0.8981 | 0.9477 |
| No log | 6.2264 | 330 | 0.8808 | 0.0979 | 0.8808 | 0.9385 |
| No log | 6.2642 | 332 | 1.0226 | 0.1515 | 1.0226 | 1.0113 |
| No log | 6.3019 | 334 | 1.2790 | 0.1282 | 1.2790 | 1.1309 |
| No log | 6.3396 | 336 | 1.4515 | 0.1084 | 1.4515 | 1.2048 |
| No log | 6.3774 | 338 | 1.3799 | 0.1056 | 1.3799 | 1.1747 |
| No log | 6.4151 | 340 | 1.0977 | 0.1212 | 1.0977 | 1.0477 |
| No log | 6.4528 | 342 | 0.9698 | 0.1331 | 0.9698 | 0.9848 |
| No log | 6.4906 | 344 | 1.0278 | 0.1161 | 1.0278 | 1.0138 |
| No log | 6.5283 | 346 | 1.2053 | 0.1282 | 1.2053 | 1.0979 |
| No log | 6.5660 | 348 | 1.4225 | 0.1345 | 1.4225 | 1.1927 |
| No log | 6.6038 | 350 | 1.4831 | 0.0893 | 1.4831 | 1.2178 |
| No log | 6.6415 | 352 | 1.3280 | 0.1546 | 1.3280 | 1.1524 |
| No log | 6.6792 | 354 | 1.2017 | 0.1549 | 1.2017 | 1.0962 |
| No log | 6.7170 | 356 | 1.0583 | 0.1145 | 1.0583 | 1.0287 |
| No log | 6.7547 | 358 | 1.0902 | 0.1145 | 1.0902 | 1.0441 |
| No log | 6.7925 | 360 | 1.2497 | 0.1158 | 1.2497 | 1.1179 |
| No log | 6.8302 | 362 | 1.5269 | 0.0303 | 1.5269 | 1.2357 |
| No log | 6.8679 | 364 | 1.7003 | -0.0222 | 1.7003 | 1.3040 |
| No log | 6.9057 | 366 | 1.6513 | 0.0567 | 1.6513 | 1.2850 |
| No log | 6.9434 | 368 | 1.4686 | 0.0256 | 1.4686 | 1.2118 |
| No log | 6.9811 | 370 | 1.3156 | 0.1220 | 1.3156 | 1.1470 |
| No log | 7.0189 | 372 | 1.2093 | 0.0882 | 1.2093 | 1.0997 |
| No log | 7.0566 | 374 | 1.1379 | 0.1825 | 1.1379 | 1.0667 |
| No log | 7.0943 | 376 | 1.2330 | 0.1280 | 1.2330 | 1.1104 |
| No log | 7.1321 | 378 | 1.4195 | 0.1083 | 1.4195 | 1.1914 |
| No log | 7.1698 | 380 | 1.4771 | 0.1531 | 1.4771 | 1.2153 |
| No log | 7.2075 | 382 | 1.4412 | 0.1788 | 1.4412 | 1.2005 |
| No log | 7.2453 | 384 | 1.3334 | 0.1220 | 1.3334 | 1.1547 |
| No log | 7.2830 | 386 | 1.3041 | 0.1220 | 1.3041 | 1.1420 |
| No log | 7.3208 | 388 | 1.2293 | 0.1161 | 1.2293 | 1.1088 |
| No log | 7.3585 | 390 | 1.2421 | 0.0929 | 1.2421 | 1.1145 |
| No log | 7.3962 | 392 | 1.2644 | 0.0929 | 1.2644 | 1.1244 |
| No log | 7.4340 | 394 | 1.3430 | 0.0959 | 1.3430 | 1.1589 |
| No log | 7.4717 | 396 | 1.4056 | 0.0438 | 1.4056 | 1.1856 |
| No log | 7.5094 | 398 | 1.4475 | -0.0033 | 1.4475 | 1.2031 |
| No log | 7.5472 | 400 | 1.4403 | -0.0221 | 1.4403 | 1.2001 |
| No log | 7.5849 | 402 | 1.3577 | 0.0489 | 1.3577 | 1.1652 |
| No log | 7.6226 | 404 | 1.2310 | 0.0929 | 1.2310 | 1.1095 |
| No log | 7.6604 | 406 | 1.1036 | 0.1212 | 1.1036 | 1.0505 |
| No log | 7.6981 | 408 | 0.9864 | 0.1128 | 0.9864 | 0.9932 |
| No log | 7.7358 | 410 | 0.9738 | 0.1111 | 0.9738 | 0.9868 |
| No log | 7.7736 | 412 | 1.0065 | 0.1128 | 1.0065 | 1.0033 |
| No log | 7.8113 | 414 | 1.0844 | 0.1212 | 1.0844 | 1.0413 |
| No log | 7.8491 | 416 | 1.1892 | 0.0929 | 1.1892 | 1.0905 |
| No log | 7.8868 | 418 | 1.2114 | 0.0929 | 1.2114 | 1.1006 |
| No log | 7.9245 | 420 | 1.2182 | 0.0929 | 1.2182 | 1.1037 |
| No log | 7.9623 | 422 | 1.2710 | 0.0929 | 1.2710 | 1.1274 |
| No log | 8.0 | 424 | 1.3455 | 0.1220 | 1.3455 | 1.1600 |
| No log | 8.0377 | 426 | 1.3804 | 0.0959 | 1.3804 | 1.1749 |
| No log | 8.0755 | 428 | 1.4080 | 0.0959 | 1.4080 | 1.1866 |
| No log | 8.1132 | 430 | 1.3368 | 0.1158 | 1.3368 | 1.1562 |
| No log | 8.1509 | 432 | 1.2962 | 0.1158 | 1.2962 | 1.1385 |
| No log | 8.1887 | 434 | 1.2718 | 0.1158 | 1.2718 | 1.1278 |
| No log | 8.2264 | 436 | 1.3273 | 0.1172 | 1.3273 | 1.1521 |
| No log | 8.2642 | 438 | 1.3533 | 0.1172 | 1.3533 | 1.1633 |
| No log | 8.3019 | 440 | 1.4342 | 0.1754 | 1.4342 | 1.1976 |
| No log | 8.3396 | 442 | 1.4681 | 0.1315 | 1.4681 | 1.2117 |
| No log | 8.3774 | 444 | 1.4573 | 0.1315 | 1.4573 | 1.2072 |
| No log | 8.4151 | 446 | 1.4251 | 0.1083 | 1.4251 | 1.1938 |
| No log | 8.4528 | 448 | 1.3656 | 0.1258 | 1.3656 | 1.1686 |
| No log | 8.4906 | 450 | 1.3532 | 0.1220 | 1.3532 | 1.1633 |
| No log | 8.5283 | 452 | 1.3487 | 0.1220 | 1.3487 | 1.1613 |
| No log | 8.5660 | 454 | 1.3230 | 0.1206 | 1.3230 | 1.1502 |
| No log | 8.6038 | 456 | 1.3715 | 0.0959 | 1.3715 | 1.1711 |
| No log | 8.6415 | 458 | 1.4432 | 0.0976 | 1.4432 | 1.2013 |
| No log | 8.6792 | 460 | 1.4968 | 0.0489 | 1.4968 | 1.2234 |
| No log | 8.7170 | 462 | 1.5278 | 0.0256 | 1.5278 | 1.2361 |
| No log | 8.7547 | 464 | 1.5098 | 0.0256 | 1.5098 | 1.2287 |
| No log | 8.7925 | 466 | 1.4302 | 0.0959 | 1.4302 | 1.1959 |
| No log | 8.8302 | 468 | 1.3284 | 0.1158 | 1.3284 | 1.1526 |
| No log | 8.8679 | 470 | 1.2818 | 0.1158 | 1.2818 | 1.1322 |
| No log | 8.9057 | 472 | 1.2461 | 0.0882 | 1.2461 | 1.1163 |
| No log | 8.9434 | 474 | 1.2325 | 0.0882 | 1.2325 | 1.1102 |
| No log | 8.9811 | 476 | 1.2464 | 0.0882 | 1.2464 | 1.1164 |
| No log | 9.0189 | 478 | 1.2714 | 0.0882 | 1.2714 | 1.1276 |
| No log | 9.0566 | 480 | 1.2808 | 0.1206 | 1.2808 | 1.1317 |
| No log | 9.0943 | 482 | 1.2996 | 0.1268 | 1.2996 | 1.1400 |
| No log | 9.1321 | 484 | 1.3464 | 0.1316 | 1.3464 | 1.1603 |
| No log | 9.1698 | 486 | 1.3709 | 0.0809 | 1.3709 | 1.1708 |
| No log | 9.2075 | 488 | 1.3614 | 0.0809 | 1.3614 | 1.1668 |
| No log | 9.2453 | 490 | 1.3317 | 0.1049 | 1.3317 | 1.1540 |
| No log | 9.2830 | 492 | 1.3324 | 0.1049 | 1.3324 | 1.1543 |
| No log | 9.3208 | 494 | 1.3265 | 0.1254 | 1.3265 | 1.1517 |
| No log | 9.3585 | 496 | 1.2951 | 0.1206 | 1.2951 | 1.1380 |
| No log | 9.3962 | 498 | 1.2687 | 0.0882 | 1.2687 | 1.1263 |
| 0.5126 | 9.4340 | 500 | 1.2577 | 0.0882 | 1.2577 | 1.1215 |
| 0.5126 | 9.4717 | 502 | 1.2489 | 0.0882 | 1.2489 | 1.1176 |
| 0.5126 | 9.5094 | 504 | 1.2480 | 0.0882 | 1.2480 | 1.1171 |
| 0.5126 | 9.5472 | 506 | 1.2582 | 0.0882 | 1.2582 | 1.1217 |
| 0.5126 | 9.5849 | 508 | 1.2834 | 0.0882 | 1.2834 | 1.1329 |
| 0.5126 | 9.6226 | 510 | 1.3013 | 0.0882 | 1.3013 | 1.1408 |
| 0.5126 | 9.6604 | 512 | 1.3245 | 0.1220 | 1.3245 | 1.1509 |
| 0.5126 | 9.6981 | 514 | 1.3305 | 0.1220 | 1.3305 | 1.1535 |
| 0.5126 | 9.7358 | 516 | 1.3243 | 0.1220 | 1.3243 | 1.1508 |
| 0.5126 | 9.7736 | 518 | 1.3141 | 0.1220 | 1.3141 | 1.1463 |
| 0.5126 | 9.8113 | 520 | 1.3083 | 0.1158 | 1.3083 | 1.1438 |
| 0.5126 | 9.8491 | 522 | 1.3029 | 0.1158 | 1.3029 | 1.1414 |
| 0.5126 | 9.8868 | 524 | 1.2914 | 0.0882 | 1.2914 | 1.1364 |
| 0.5126 | 9.9245 | 526 | 1.2797 | 0.0882 | 1.2797 | 1.1312 |
| 0.5126 | 9.9623 | 528 | 1.2712 | 0.0882 | 1.2712 | 1.1275 |
| 0.5126 | 10.0 | 530 | 1.2680 | 0.0882 | 1.2680 | 1.1260 |
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_run3_AugV5_k12_task3_organization
Base model
aubmindlab/bert-base-arabertv02