Instructions to use MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k9_task3_organization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k9_task3_organization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k9_task3_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k9_task3_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k9_task3_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k9_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: 0.5685
- Qwk: 0.3563
- Mse: 0.5685
- Rmse: 0.7540
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 | 0.0435 | 2 | 3.3614 | -0.0160 | 3.3614 | 1.8334 |
| No log | 0.0870 | 4 | 1.8721 | -0.0390 | 1.8721 | 1.3683 |
| No log | 0.1304 | 6 | 1.0439 | 0.0294 | 1.0439 | 1.0217 |
| No log | 0.1739 | 8 | 0.8095 | 0.2000 | 0.8095 | 0.8997 |
| No log | 0.2174 | 10 | 0.6153 | 0.0 | 0.6153 | 0.7844 |
| No log | 0.2609 | 12 | 0.6953 | 0.1385 | 0.6953 | 0.8338 |
| No log | 0.3043 | 14 | 0.6392 | 0.0 | 0.6392 | 0.7995 |
| No log | 0.3478 | 16 | 0.7709 | 0.2000 | 0.7709 | 0.8780 |
| No log | 0.3913 | 18 | 0.9457 | 0.1013 | 0.9457 | 0.9725 |
| No log | 0.4348 | 20 | 0.8840 | 0.0884 | 0.8840 | 0.9402 |
| No log | 0.4783 | 22 | 0.7620 | 0.1923 | 0.7620 | 0.8729 |
| No log | 0.5217 | 24 | 0.6859 | 0.0164 | 0.6859 | 0.8282 |
| No log | 0.5652 | 26 | 0.9516 | 0.0545 | 0.9516 | 0.9755 |
| No log | 0.6087 | 28 | 0.9485 | 0.0909 | 0.9485 | 0.9739 |
| No log | 0.6522 | 30 | 0.7936 | 0.1746 | 0.7936 | 0.8908 |
| No log | 0.6957 | 32 | 0.7897 | 0.2077 | 0.7897 | 0.8887 |
| No log | 0.7391 | 34 | 0.7334 | 0.2332 | 0.7334 | 0.8564 |
| No log | 0.7826 | 36 | 0.6472 | 0.0409 | 0.6472 | 0.8045 |
| No log | 0.8261 | 38 | 0.7738 | 0.2457 | 0.7738 | 0.8797 |
| No log | 0.8696 | 40 | 0.7260 | 0.2000 | 0.7260 | 0.8521 |
| No log | 0.9130 | 42 | 0.6166 | 0.2000 | 0.6166 | 0.7852 |
| No log | 0.9565 | 44 | 0.7081 | 0.2157 | 0.7081 | 0.8415 |
| No log | 1.0 | 46 | 0.5771 | 0.2000 | 0.5771 | 0.7596 |
| No log | 1.0435 | 48 | 0.5847 | 0.2113 | 0.5847 | 0.7647 |
| No log | 1.0870 | 50 | 0.5740 | 0.1781 | 0.5740 | 0.7576 |
| No log | 1.1304 | 52 | 0.5991 | 0.2222 | 0.5991 | 0.7740 |
| No log | 1.1739 | 54 | 0.8272 | 0.1154 | 0.8272 | 0.9095 |
| No log | 1.2174 | 56 | 0.6854 | 0.2281 | 0.6854 | 0.8279 |
| No log | 1.2609 | 58 | 0.7888 | 0.2554 | 0.7888 | 0.8881 |
| No log | 1.3043 | 60 | 0.9383 | 0.1736 | 0.9383 | 0.9687 |
| No log | 1.3478 | 62 | 0.6270 | 0.2273 | 0.6270 | 0.7918 |
| No log | 1.3913 | 64 | 0.9108 | 0.0175 | 0.9108 | 0.9544 |
| No log | 1.4348 | 66 | 1.0522 | 0.0183 | 1.0522 | 1.0257 |
| No log | 1.4783 | 68 | 0.6989 | 0.2405 | 0.6989 | 0.8360 |
| No log | 1.5217 | 70 | 0.6793 | 0.1304 | 0.6793 | 0.8242 |
| No log | 1.5652 | 72 | 0.8659 | 0.2000 | 0.8659 | 0.9305 |
| No log | 1.6087 | 74 | 0.6544 | 0.0980 | 0.6544 | 0.8089 |
| No log | 1.6522 | 76 | 0.5739 | 0.2848 | 0.5739 | 0.7575 |
| No log | 1.6957 | 78 | 0.6443 | 0.2360 | 0.6443 | 0.8027 |
| No log | 1.7391 | 80 | 0.7775 | 0.1527 | 0.7775 | 0.8818 |
| No log | 1.7826 | 82 | 0.6638 | 0.2670 | 0.6638 | 0.8147 |
| No log | 1.8261 | 84 | 0.6875 | 0.2670 | 0.6875 | 0.8292 |
| No log | 1.8696 | 86 | 0.5989 | 0.3831 | 0.5989 | 0.7739 |
| No log | 1.9130 | 88 | 0.6996 | 0.3301 | 0.6996 | 0.8364 |
| No log | 1.9565 | 90 | 0.7846 | 0.2676 | 0.7846 | 0.8858 |
| No log | 2.0 | 92 | 0.6312 | 0.3498 | 0.6312 | 0.7945 |
| No log | 2.0435 | 94 | 0.6077 | 0.3641 | 0.6077 | 0.7795 |
| No log | 2.0870 | 96 | 0.5708 | 0.4167 | 0.5708 | 0.7555 |
| No log | 2.1304 | 98 | 1.1233 | 0.1945 | 1.1233 | 1.0599 |
| No log | 2.1739 | 100 | 1.7486 | 0.1756 | 1.7486 | 1.3224 |
| No log | 2.2174 | 102 | 1.1572 | 0.1724 | 1.1572 | 1.0757 |
| No log | 2.2609 | 104 | 0.5441 | 0.2688 | 0.5441 | 0.7376 |
| No log | 2.3043 | 106 | 0.5866 | 0.3077 | 0.5866 | 0.7659 |
| No log | 2.3478 | 108 | 0.5742 | 0.2709 | 0.5742 | 0.7577 |
| No log | 2.3913 | 110 | 0.6090 | 0.2670 | 0.6090 | 0.7804 |
| No log | 2.4348 | 112 | 1.0646 | 0.1331 | 1.0646 | 1.0318 |
| No log | 2.4783 | 114 | 0.8726 | 0.2479 | 0.8726 | 0.9341 |
| No log | 2.5217 | 116 | 0.6104 | 0.3641 | 0.6104 | 0.7813 |
| No log | 2.5652 | 118 | 0.7713 | 0.1579 | 0.7713 | 0.8782 |
| No log | 2.6087 | 120 | 0.6311 | 0.2607 | 0.6311 | 0.7944 |
| No log | 2.6522 | 122 | 0.6197 | 0.3636 | 0.6197 | 0.7872 |
| No log | 2.6957 | 124 | 0.8253 | 0.1050 | 0.8253 | 0.9085 |
| No log | 2.7391 | 126 | 0.7567 | 0.2245 | 0.7567 | 0.8699 |
| No log | 2.7826 | 128 | 0.5691 | 0.3829 | 0.5691 | 0.7544 |
| No log | 2.8261 | 130 | 0.7863 | 0.2340 | 0.7863 | 0.8867 |
| No log | 2.8696 | 132 | 0.7521 | 0.1861 | 0.7521 | 0.8673 |
| No log | 2.9130 | 134 | 0.5707 | 0.3371 | 0.5707 | 0.7555 |
| No log | 2.9565 | 136 | 1.2137 | 0.1392 | 1.2137 | 1.1017 |
| No log | 3.0 | 138 | 1.7147 | 0.1169 | 1.7147 | 1.3095 |
| No log | 3.0435 | 140 | 1.2447 | 0.1605 | 1.2447 | 1.1156 |
| No log | 3.0870 | 142 | 0.6796 | 0.1841 | 0.6796 | 0.8244 |
| No log | 3.1304 | 144 | 0.6719 | 0.2563 | 0.6719 | 0.8197 |
| No log | 3.1739 | 146 | 0.6109 | 0.3446 | 0.6109 | 0.7816 |
| No log | 3.2174 | 148 | 0.7422 | 0.2523 | 0.7422 | 0.8615 |
| No log | 3.2609 | 150 | 0.9579 | 0.1000 | 0.9579 | 0.9787 |
| No log | 3.3043 | 152 | 0.6802 | 0.2077 | 0.6802 | 0.8247 |
| No log | 3.3478 | 154 | 0.5499 | 0.4409 | 0.5499 | 0.7415 |
| No log | 3.3913 | 156 | 0.5598 | 0.3575 | 0.5598 | 0.7482 |
| No log | 3.4348 | 158 | 0.6054 | 0.4167 | 0.6054 | 0.7781 |
| No log | 3.4783 | 160 | 0.8931 | 0.1220 | 0.8931 | 0.9450 |
| No log | 3.5217 | 162 | 1.2845 | 0.2047 | 1.2845 | 1.1334 |
| No log | 3.5652 | 164 | 0.9893 | 0.2000 | 0.9893 | 0.9946 |
| No log | 3.6087 | 166 | 0.5816 | 0.4468 | 0.5816 | 0.7627 |
| No log | 3.6522 | 168 | 0.6101 | 0.3846 | 0.6101 | 0.7811 |
| No log | 3.6957 | 170 | 0.5634 | 0.4227 | 0.5634 | 0.7506 |
| No log | 3.7391 | 172 | 0.8291 | 0.2131 | 0.8291 | 0.9105 |
| No log | 3.7826 | 174 | 0.9333 | 0.1571 | 0.9333 | 0.9661 |
| No log | 3.8261 | 176 | 0.7144 | 0.3028 | 0.7144 | 0.8452 |
| No log | 3.8696 | 178 | 0.6455 | 0.3398 | 0.6455 | 0.8034 |
| No log | 3.9130 | 180 | 0.6278 | 0.3333 | 0.6278 | 0.7924 |
| No log | 3.9565 | 182 | 0.6167 | 0.3035 | 0.6167 | 0.7853 |
| No log | 4.0 | 184 | 0.7679 | 0.2607 | 0.7679 | 0.8763 |
| No log | 4.0435 | 186 | 0.7369 | 0.1921 | 0.7369 | 0.8584 |
| No log | 4.0870 | 188 | 0.5816 | 0.4098 | 0.5816 | 0.7626 |
| No log | 4.1304 | 190 | 0.5903 | 0.4667 | 0.5903 | 0.7683 |
| No log | 4.1739 | 192 | 0.6653 | 0.3663 | 0.6653 | 0.8157 |
| No log | 4.2174 | 194 | 0.5865 | 0.4286 | 0.5865 | 0.7658 |
| No log | 4.2609 | 196 | 0.6135 | 0.4112 | 0.6135 | 0.7832 |
| No log | 4.3043 | 198 | 0.8729 | 0.2424 | 0.8729 | 0.9343 |
| No log | 4.3478 | 200 | 0.9214 | 0.2424 | 0.9214 | 0.9599 |
| No log | 4.3913 | 202 | 0.8314 | 0.2131 | 0.8314 | 0.9118 |
| No log | 4.4348 | 204 | 0.6700 | 0.3684 | 0.6700 | 0.8185 |
| No log | 4.4783 | 206 | 0.5716 | 0.2917 | 0.5716 | 0.7561 |
| No log | 4.5217 | 208 | 0.5655 | 0.3073 | 0.5655 | 0.7520 |
| No log | 4.5652 | 210 | 0.6085 | 0.4639 | 0.6085 | 0.7801 |
| No log | 4.6087 | 212 | 0.6196 | 0.4043 | 0.6196 | 0.7872 |
| No log | 4.6522 | 214 | 0.6272 | 0.3297 | 0.6272 | 0.7919 |
| No log | 4.6957 | 216 | 0.5821 | 0.4652 | 0.5821 | 0.7630 |
| No log | 4.7391 | 218 | 0.6324 | 0.2153 | 0.6324 | 0.7952 |
| No log | 4.7826 | 220 | 0.7294 | 0.2696 | 0.7294 | 0.8540 |
| No log | 4.8261 | 222 | 0.6313 | 0.1921 | 0.6313 | 0.7946 |
| No log | 4.8696 | 224 | 0.6774 | 0.2941 | 0.6774 | 0.8231 |
| No log | 4.9130 | 226 | 0.8791 | 0.1803 | 0.8791 | 0.9376 |
| No log | 4.9565 | 228 | 0.7429 | 0.3247 | 0.7429 | 0.8619 |
| No log | 5.0 | 230 | 0.6096 | 0.4652 | 0.6096 | 0.7808 |
| No log | 5.0435 | 232 | 0.6137 | 0.4583 | 0.6137 | 0.7834 |
| No log | 5.0870 | 234 | 0.6207 | 0.4112 | 0.6207 | 0.7879 |
| No log | 5.1304 | 236 | 0.7437 | 0.2881 | 0.7437 | 0.8624 |
| No log | 5.1739 | 238 | 0.9417 | 0.2061 | 0.9417 | 0.9704 |
| No log | 5.2174 | 240 | 0.9301 | 0.2296 | 0.9301 | 0.9644 |
| No log | 5.2609 | 242 | 0.6927 | 0.2762 | 0.6927 | 0.8323 |
| No log | 5.3043 | 244 | 0.5403 | 0.4667 | 0.5403 | 0.7350 |
| No log | 5.3478 | 246 | 0.5241 | 0.5410 | 0.5241 | 0.7240 |
| No log | 5.3913 | 248 | 0.5497 | 0.3118 | 0.5497 | 0.7414 |
| No log | 5.4348 | 250 | 0.7279 | 0.1845 | 0.7279 | 0.8532 |
| No log | 5.4783 | 252 | 0.8306 | 0.2389 | 0.8306 | 0.9114 |
| No log | 5.5217 | 254 | 0.6764 | 0.2850 | 0.6764 | 0.8224 |
| No log | 5.5652 | 256 | 0.5364 | 0.5052 | 0.5364 | 0.7324 |
| No log | 5.6087 | 258 | 0.5666 | 0.4450 | 0.5666 | 0.7527 |
| No log | 5.6522 | 260 | 0.5455 | 0.4680 | 0.5455 | 0.7386 |
| No log | 5.6957 | 262 | 0.6283 | 0.3333 | 0.6283 | 0.7927 |
| No log | 5.7391 | 264 | 0.9378 | 0.2672 | 0.9378 | 0.9684 |
| No log | 5.7826 | 266 | 0.9672 | 0.2195 | 0.9672 | 0.9835 |
| No log | 5.8261 | 268 | 0.7547 | 0.1698 | 0.7547 | 0.8687 |
| No log | 5.8696 | 270 | 0.5969 | 0.4105 | 0.5969 | 0.7726 |
| No log | 5.9130 | 272 | 0.5818 | 0.4105 | 0.5818 | 0.7628 |
| No log | 5.9565 | 274 | 0.6260 | 0.2871 | 0.6260 | 0.7912 |
| No log | 6.0 | 276 | 0.7637 | 0.2233 | 0.7637 | 0.8739 |
| No log | 6.0435 | 278 | 0.7327 | 0.2637 | 0.7327 | 0.8560 |
| No log | 6.0870 | 280 | 0.6040 | 0.2766 | 0.6040 | 0.7771 |
| No log | 6.1304 | 282 | 0.5578 | 0.4595 | 0.5578 | 0.7469 |
| No log | 6.1739 | 284 | 0.5720 | 0.4225 | 0.5720 | 0.7563 |
| No log | 6.2174 | 286 | 0.6293 | 0.24 | 0.6293 | 0.7933 |
| No log | 6.2609 | 288 | 0.6721 | 0.2871 | 0.6721 | 0.8198 |
| No log | 6.3043 | 290 | 0.6125 | 0.2821 | 0.6125 | 0.7826 |
| No log | 6.3478 | 292 | 0.5572 | 0.4105 | 0.5572 | 0.7465 |
| No log | 6.3913 | 294 | 0.5604 | 0.4105 | 0.5604 | 0.7486 |
| No log | 6.4348 | 296 | 0.5773 | 0.3016 | 0.5773 | 0.7598 |
| No log | 6.4783 | 298 | 0.5972 | 0.2842 | 0.5972 | 0.7728 |
| No log | 6.5217 | 300 | 0.6351 | 0.3333 | 0.6351 | 0.7969 |
| No log | 6.5652 | 302 | 0.7471 | 0.1921 | 0.7471 | 0.8643 |
| No log | 6.6087 | 304 | 0.7978 | 0.1923 | 0.7978 | 0.8932 |
| No log | 6.6522 | 306 | 0.7102 | 0.2563 | 0.7102 | 0.8427 |
| No log | 6.6957 | 308 | 0.5653 | 0.3641 | 0.5653 | 0.7519 |
| No log | 6.7391 | 310 | 0.5800 | 0.3575 | 0.5800 | 0.7616 |
| No log | 6.7826 | 312 | 0.6045 | 0.4171 | 0.6045 | 0.7775 |
| No log | 6.8261 | 314 | 0.5635 | 0.3913 | 0.5635 | 0.7506 |
| No log | 6.8696 | 316 | 0.5930 | 0.3089 | 0.5930 | 0.7700 |
| No log | 6.9130 | 318 | 0.6418 | 0.3043 | 0.6418 | 0.8011 |
| No log | 6.9565 | 320 | 0.6449 | 0.3043 | 0.6449 | 0.8030 |
| No log | 7.0 | 322 | 0.6182 | 0.2513 | 0.6182 | 0.7862 |
| No log | 7.0435 | 324 | 0.5559 | 0.3073 | 0.5559 | 0.7456 |
| No log | 7.0870 | 326 | 0.5467 | 0.4286 | 0.5467 | 0.7394 |
| No log | 7.1304 | 328 | 0.5620 | 0.3073 | 0.5620 | 0.7497 |
| No log | 7.1739 | 330 | 0.6108 | 0.3073 | 0.6108 | 0.7815 |
| No log | 7.2174 | 332 | 0.6036 | 0.2527 | 0.6036 | 0.7769 |
| No log | 7.2609 | 334 | 0.5809 | 0.3089 | 0.5809 | 0.7622 |
| No log | 7.3043 | 336 | 0.5622 | 0.3708 | 0.5622 | 0.7498 |
| No log | 7.3478 | 338 | 0.5735 | 0.4033 | 0.5735 | 0.7573 |
| No log | 7.3913 | 340 | 0.5839 | 0.4033 | 0.5839 | 0.7641 |
| No log | 7.4348 | 342 | 0.5868 | 0.3191 | 0.5868 | 0.7660 |
| No log | 7.4783 | 344 | 0.6688 | 0.2746 | 0.6688 | 0.8178 |
| No log | 7.5217 | 346 | 0.8565 | 0.2531 | 0.8565 | 0.9255 |
| No log | 7.5652 | 348 | 0.9341 | 0.2195 | 0.9341 | 0.9665 |
| No log | 7.6087 | 350 | 0.8668 | 0.2531 | 0.8668 | 0.9310 |
| No log | 7.6522 | 352 | 0.7072 | 0.2475 | 0.7072 | 0.8409 |
| No log | 7.6957 | 354 | 0.5987 | 0.3641 | 0.5987 | 0.7738 |
| No log | 7.7391 | 356 | 0.5916 | 0.3978 | 0.5916 | 0.7691 |
| No log | 7.7826 | 358 | 0.5869 | 0.3913 | 0.5869 | 0.7661 |
| No log | 7.8261 | 360 | 0.5727 | 0.2865 | 0.5727 | 0.7568 |
| No log | 7.8696 | 362 | 0.6061 | 0.3224 | 0.6061 | 0.7785 |
| No log | 7.9130 | 364 | 0.6836 | 0.2990 | 0.6836 | 0.8268 |
| No log | 7.9565 | 366 | 0.7244 | 0.2245 | 0.7244 | 0.8511 |
| No log | 8.0 | 368 | 0.6974 | 0.2990 | 0.6974 | 0.8351 |
| No log | 8.0435 | 370 | 0.6361 | 0.3478 | 0.6361 | 0.7976 |
| No log | 8.0870 | 372 | 0.5751 | 0.2914 | 0.5751 | 0.7584 |
| No log | 8.1304 | 374 | 0.5405 | 0.3333 | 0.5405 | 0.7352 |
| No log | 8.1739 | 376 | 0.5395 | 0.3708 | 0.5395 | 0.7345 |
| No log | 8.2174 | 378 | 0.5357 | 0.3708 | 0.5357 | 0.7319 |
| No log | 8.2609 | 380 | 0.5405 | 0.3563 | 0.5405 | 0.7352 |
| No log | 8.3043 | 382 | 0.5991 | 0.3563 | 0.5991 | 0.7740 |
| No log | 8.3478 | 384 | 0.7212 | 0.2563 | 0.7212 | 0.8493 |
| No log | 8.3913 | 386 | 0.7991 | 0.1610 | 0.7991 | 0.8939 |
| No log | 8.4348 | 388 | 0.7831 | 0.1600 | 0.7831 | 0.8849 |
| No log | 8.4783 | 390 | 0.6990 | 0.3016 | 0.6990 | 0.8360 |
| No log | 8.5217 | 392 | 0.5988 | 0.3073 | 0.5988 | 0.7738 |
| No log | 8.5652 | 394 | 0.5596 | 0.3978 | 0.5596 | 0.7481 |
| No log | 8.6087 | 396 | 0.5391 | 0.3478 | 0.5391 | 0.7342 |
| No log | 8.6522 | 398 | 0.5403 | 0.3591 | 0.5403 | 0.7351 |
| No log | 8.6957 | 400 | 0.5576 | 0.3978 | 0.5576 | 0.7467 |
| No log | 8.7391 | 402 | 0.5801 | 0.3898 | 0.5801 | 0.7617 |
| No log | 8.7826 | 404 | 0.6163 | 0.3016 | 0.6163 | 0.7850 |
| No log | 8.8261 | 406 | 0.6574 | 0.3016 | 0.6574 | 0.8108 |
| No log | 8.8696 | 408 | 0.6530 | 0.3016 | 0.6530 | 0.8081 |
| No log | 8.9130 | 410 | 0.6243 | 0.3016 | 0.6243 | 0.7901 |
| No log | 8.9565 | 412 | 0.6116 | 0.3016 | 0.6116 | 0.7820 |
| No log | 9.0 | 414 | 0.5900 | 0.3073 | 0.5900 | 0.7681 |
| No log | 9.0435 | 416 | 0.5682 | 0.2994 | 0.5682 | 0.7538 |
| No log | 9.0870 | 418 | 0.5468 | 0.3661 | 0.5468 | 0.7395 |
| No log | 9.1304 | 420 | 0.5361 | 0.3478 | 0.5361 | 0.7322 |
| No log | 9.1739 | 422 | 0.5347 | 0.3478 | 0.5347 | 0.7312 |
| No log | 9.2174 | 424 | 0.5382 | 0.3591 | 0.5382 | 0.7336 |
| No log | 9.2609 | 426 | 0.5464 | 0.3661 | 0.5464 | 0.7392 |
| No log | 9.3043 | 428 | 0.5617 | 0.2994 | 0.5617 | 0.7495 |
| No log | 9.3478 | 430 | 0.5783 | 0.3563 | 0.5783 | 0.7605 |
| No log | 9.3913 | 432 | 0.5980 | 0.3043 | 0.5980 | 0.7733 |
| No log | 9.4348 | 434 | 0.6090 | 0.3016 | 0.6090 | 0.7804 |
| No log | 9.4783 | 436 | 0.6105 | 0.3016 | 0.6105 | 0.7813 |
| No log | 9.5217 | 438 | 0.6043 | 0.3043 | 0.6043 | 0.7774 |
| No log | 9.5652 | 440 | 0.5941 | 0.3563 | 0.5941 | 0.7708 |
| No log | 9.6087 | 442 | 0.5832 | 0.3563 | 0.5832 | 0.7637 |
| No log | 9.6522 | 444 | 0.5731 | 0.3563 | 0.5731 | 0.7570 |
| No log | 9.6957 | 446 | 0.5686 | 0.3563 | 0.5686 | 0.7540 |
| No log | 9.7391 | 448 | 0.5666 | 0.3563 | 0.5666 | 0.7527 |
| No log | 9.7826 | 450 | 0.5652 | 0.3563 | 0.5652 | 0.7518 |
| No log | 9.8261 | 452 | 0.5661 | 0.3563 | 0.5661 | 0.7524 |
| No log | 9.8696 | 454 | 0.5673 | 0.3563 | 0.5673 | 0.7532 |
| No log | 9.9130 | 456 | 0.5683 | 0.3563 | 0.5683 | 0.7538 |
| No log | 9.9565 | 458 | 0.5685 | 0.3563 | 0.5685 | 0.7540 |
| No log | 10.0 | 460 | 0.5685 | 0.3563 | 0.5685 | 0.7540 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k9_task3_organization
Base model
aubmindlab/bert-base-arabertv02