Instructions to use MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k16_task5_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_k16_task5_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_k16_task5_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k16_task5_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k16_task5_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k16_task5_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: 1.0305
- Qwk: 0.6551
- Mse: 1.0305
- Rmse: 1.0151
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 | 2.2489 | 0.0523 | 2.2489 | 1.4996 |
| No log | 0.0755 | 4 | 1.4613 | 0.1815 | 1.4613 | 1.2088 |
| No log | 0.1132 | 6 | 1.3887 | 0.1575 | 1.3887 | 1.1784 |
| No log | 0.1509 | 8 | 1.4162 | 0.2015 | 1.4162 | 1.1900 |
| No log | 0.1887 | 10 | 1.5631 | 0.3510 | 1.5631 | 1.2502 |
| No log | 0.2264 | 12 | 1.6306 | 0.3322 | 1.6306 | 1.2769 |
| No log | 0.2642 | 14 | 1.5097 | 0.1666 | 1.5097 | 1.2287 |
| No log | 0.3019 | 16 | 1.4299 | 0.1711 | 1.4299 | 1.1958 |
| No log | 0.3396 | 18 | 1.4116 | 0.1258 | 1.4116 | 1.1881 |
| No log | 0.3774 | 20 | 1.4241 | 0.1711 | 1.4241 | 1.1934 |
| No log | 0.4151 | 22 | 1.5291 | 0.3109 | 1.5291 | 1.2366 |
| No log | 0.4528 | 24 | 1.6232 | 0.3769 | 1.6232 | 1.2740 |
| No log | 0.4906 | 26 | 1.7126 | 0.3318 | 1.7126 | 1.3087 |
| No log | 0.5283 | 28 | 1.7142 | 0.3329 | 1.7142 | 1.3093 |
| No log | 0.5660 | 30 | 1.6618 | 0.3950 | 1.6618 | 1.2891 |
| No log | 0.6038 | 32 | 1.6418 | 0.3853 | 1.6418 | 1.2813 |
| No log | 0.6415 | 34 | 1.5816 | 0.3134 | 1.5816 | 1.2576 |
| No log | 0.6792 | 36 | 1.5473 | 0.3101 | 1.5473 | 1.2439 |
| No log | 0.7170 | 38 | 1.6520 | 0.3439 | 1.6520 | 1.2853 |
| No log | 0.7547 | 40 | 1.8531 | 0.3136 | 1.8531 | 1.3613 |
| No log | 0.7925 | 42 | 1.9959 | 0.2766 | 1.9959 | 1.4127 |
| No log | 0.8302 | 44 | 1.8526 | 0.3054 | 1.8526 | 1.3611 |
| No log | 0.8679 | 46 | 1.5661 | 0.3614 | 1.5661 | 1.2514 |
| No log | 0.9057 | 48 | 1.3676 | 0.4335 | 1.3676 | 1.1695 |
| No log | 0.9434 | 50 | 1.2637 | 0.4656 | 1.2637 | 1.1241 |
| No log | 0.9811 | 52 | 1.1884 | 0.5170 | 1.1884 | 1.0902 |
| No log | 1.0189 | 54 | 1.3761 | 0.4555 | 1.3761 | 1.1731 |
| No log | 1.0566 | 56 | 1.6777 | 0.4420 | 1.6777 | 1.2953 |
| No log | 1.0943 | 58 | 1.8271 | 0.4294 | 1.8271 | 1.3517 |
| No log | 1.1321 | 60 | 1.6343 | 0.4685 | 1.6343 | 1.2784 |
| No log | 1.1698 | 62 | 1.6703 | 0.4778 | 1.6703 | 1.2924 |
| No log | 1.2075 | 64 | 1.8927 | 0.4393 | 1.8927 | 1.3757 |
| No log | 1.2453 | 66 | 1.8382 | 0.4390 | 1.8382 | 1.3558 |
| No log | 1.2830 | 68 | 1.7684 | 0.4355 | 1.7684 | 1.3298 |
| No log | 1.3208 | 70 | 1.6071 | 0.4780 | 1.6071 | 1.2677 |
| No log | 1.3585 | 72 | 1.3052 | 0.5144 | 1.3052 | 1.1424 |
| No log | 1.3962 | 74 | 1.1610 | 0.5357 | 1.1610 | 1.0775 |
| No log | 1.4340 | 76 | 1.3523 | 0.5010 | 1.3523 | 1.1629 |
| No log | 1.4717 | 78 | 1.9282 | 0.4741 | 1.9282 | 1.3886 |
| No log | 1.5094 | 80 | 2.2271 | 0.4607 | 2.2271 | 1.4924 |
| No log | 1.5472 | 82 | 2.1050 | 0.4721 | 2.1050 | 1.4509 |
| No log | 1.5849 | 84 | 1.6810 | 0.4981 | 1.6810 | 1.2965 |
| No log | 1.6226 | 86 | 1.6228 | 0.4886 | 1.6228 | 1.2739 |
| No log | 1.6604 | 88 | 1.7947 | 0.4825 | 1.7947 | 1.3396 |
| No log | 1.6981 | 90 | 1.9372 | 0.4598 | 1.9372 | 1.3918 |
| No log | 1.7358 | 92 | 1.9144 | 0.4814 | 1.9144 | 1.3836 |
| No log | 1.7736 | 94 | 1.7176 | 0.4994 | 1.7176 | 1.3106 |
| No log | 1.8113 | 96 | 1.6005 | 0.5429 | 1.6005 | 1.2651 |
| No log | 1.8491 | 98 | 1.3956 | 0.5780 | 1.3956 | 1.1814 |
| No log | 1.8868 | 100 | 1.1335 | 0.6136 | 1.1335 | 1.0646 |
| No log | 1.9245 | 102 | 1.1253 | 0.6099 | 1.1253 | 1.0608 |
| No log | 1.9623 | 104 | 1.0380 | 0.6665 | 1.0380 | 1.0188 |
| No log | 2.0 | 106 | 1.0993 | 0.6122 | 1.0993 | 1.0485 |
| No log | 2.0377 | 108 | 1.2437 | 0.5880 | 1.2437 | 1.1152 |
| No log | 2.0755 | 110 | 1.2914 | 0.6062 | 1.2914 | 1.1364 |
| No log | 2.1132 | 112 | 1.4993 | 0.5623 | 1.4993 | 1.2245 |
| No log | 2.1509 | 114 | 1.6392 | 0.5531 | 1.6392 | 1.2803 |
| No log | 2.1887 | 116 | 1.6710 | 0.5435 | 1.6710 | 1.2927 |
| No log | 2.2264 | 118 | 1.5656 | 0.5552 | 1.5656 | 1.2512 |
| No log | 2.2642 | 120 | 1.3433 | 0.5727 | 1.3433 | 1.1590 |
| No log | 2.3019 | 122 | 1.3008 | 0.5652 | 1.3008 | 1.1405 |
| No log | 2.3396 | 124 | 1.2348 | 0.5775 | 1.2348 | 1.1112 |
| No log | 2.3774 | 126 | 1.2530 | 0.5794 | 1.2530 | 1.1194 |
| No log | 2.4151 | 128 | 1.4128 | 0.5474 | 1.4128 | 1.1886 |
| No log | 2.4528 | 130 | 1.4242 | 0.5460 | 1.4242 | 1.1934 |
| No log | 2.4906 | 132 | 1.2559 | 0.5603 | 1.2559 | 1.1207 |
| No log | 2.5283 | 134 | 1.1743 | 0.5736 | 1.1743 | 1.0836 |
| No log | 2.5660 | 136 | 1.4004 | 0.5517 | 1.4004 | 1.1834 |
| No log | 2.6038 | 138 | 1.4112 | 0.5561 | 1.4112 | 1.1879 |
| No log | 2.6415 | 140 | 1.4058 | 0.5540 | 1.4058 | 1.1857 |
| No log | 2.6792 | 142 | 1.2767 | 0.5668 | 1.2767 | 1.1299 |
| No log | 2.7170 | 144 | 1.1000 | 0.5906 | 1.1000 | 1.0488 |
| No log | 2.7547 | 146 | 1.0977 | 0.5873 | 1.0977 | 1.0477 |
| No log | 2.7925 | 148 | 1.1819 | 0.5688 | 1.1819 | 1.0872 |
| No log | 2.8302 | 150 | 1.1415 | 0.5805 | 1.1415 | 1.0684 |
| No log | 2.8679 | 152 | 0.9421 | 0.6606 | 0.9421 | 0.9706 |
| No log | 2.9057 | 154 | 0.9357 | 0.6606 | 0.9357 | 0.9673 |
| No log | 2.9434 | 156 | 0.9567 | 0.6517 | 0.9567 | 0.9781 |
| No log | 2.9811 | 158 | 1.0113 | 0.6263 | 1.0113 | 1.0056 |
| No log | 3.0189 | 160 | 0.9716 | 0.6470 | 0.9716 | 0.9857 |
| No log | 3.0566 | 162 | 1.1657 | 0.5965 | 1.1657 | 1.0797 |
| No log | 3.0943 | 164 | 1.4857 | 0.5788 | 1.4857 | 1.2189 |
| No log | 3.1321 | 166 | 1.3372 | 0.5736 | 1.3372 | 1.1564 |
| No log | 3.1698 | 168 | 1.0424 | 0.6261 | 1.0424 | 1.0210 |
| No log | 3.2075 | 170 | 0.8925 | 0.6723 | 0.8925 | 0.9447 |
| No log | 3.2453 | 172 | 0.9996 | 0.6496 | 0.9996 | 0.9998 |
| No log | 3.2830 | 174 | 1.2459 | 0.5688 | 1.2459 | 1.1162 |
| No log | 3.3208 | 176 | 1.5709 | 0.5344 | 1.5709 | 1.2533 |
| No log | 3.3585 | 178 | 1.4943 | 0.5453 | 1.4943 | 1.2224 |
| No log | 3.3962 | 180 | 1.2409 | 0.5717 | 1.2409 | 1.1139 |
| No log | 3.4340 | 182 | 0.9447 | 0.6723 | 0.9447 | 0.9720 |
| No log | 3.4717 | 184 | 0.8838 | 0.6861 | 0.8838 | 0.9401 |
| No log | 3.5094 | 186 | 1.0212 | 0.6087 | 1.0212 | 1.0106 |
| No log | 3.5472 | 188 | 1.1176 | 0.6071 | 1.1176 | 1.0571 |
| No log | 3.5849 | 190 | 1.0193 | 0.6127 | 1.0193 | 1.0096 |
| No log | 3.6226 | 192 | 0.9680 | 0.6299 | 0.9680 | 0.9839 |
| No log | 3.6604 | 194 | 0.8807 | 0.6884 | 0.8807 | 0.9385 |
| No log | 3.6981 | 196 | 0.9119 | 0.6768 | 0.9119 | 0.9549 |
| No log | 3.7358 | 198 | 1.0068 | 0.6418 | 1.0068 | 1.0034 |
| No log | 3.7736 | 200 | 1.1086 | 0.6010 | 1.1086 | 1.0529 |
| No log | 3.8113 | 202 | 1.1588 | 0.6010 | 1.1588 | 1.0765 |
| No log | 3.8491 | 204 | 1.0283 | 0.6207 | 1.0283 | 1.0140 |
| No log | 3.8868 | 206 | 0.9186 | 0.6552 | 0.9186 | 0.9584 |
| No log | 3.9245 | 208 | 0.8751 | 0.6592 | 0.8751 | 0.9355 |
| No log | 3.9623 | 210 | 1.0037 | 0.6269 | 1.0037 | 1.0019 |
| No log | 4.0 | 212 | 1.3478 | 0.5711 | 1.3478 | 1.1609 |
| No log | 4.0377 | 214 | 1.6939 | 0.5245 | 1.6939 | 1.3015 |
| No log | 4.0755 | 216 | 1.7118 | 0.5355 | 1.7118 | 1.3084 |
| No log | 4.1132 | 218 | 1.4254 | 0.5635 | 1.4254 | 1.1939 |
| No log | 4.1509 | 220 | 1.0777 | 0.6282 | 1.0777 | 1.0381 |
| No log | 4.1887 | 222 | 0.8408 | 0.6797 | 0.8408 | 0.9169 |
| No log | 4.2264 | 224 | 0.8388 | 0.6616 | 0.8388 | 0.9159 |
| No log | 4.2642 | 226 | 0.9955 | 0.6263 | 0.9955 | 0.9977 |
| No log | 4.3019 | 228 | 1.3300 | 0.5797 | 1.3300 | 1.1532 |
| No log | 4.3396 | 230 | 1.7166 | 0.5259 | 1.7166 | 1.3102 |
| No log | 4.3774 | 232 | 1.7946 | 0.5181 | 1.7946 | 1.3396 |
| No log | 4.4151 | 234 | 1.6453 | 0.5336 | 1.6453 | 1.2827 |
| No log | 4.4528 | 236 | 1.3464 | 0.5557 | 1.3464 | 1.1603 |
| No log | 4.4906 | 238 | 1.1362 | 0.5928 | 1.1362 | 1.0659 |
| No log | 4.5283 | 240 | 1.0531 | 0.6359 | 1.0531 | 1.0262 |
| No log | 4.5660 | 242 | 1.1252 | 0.5897 | 1.1252 | 1.0608 |
| No log | 4.6038 | 244 | 1.1043 | 0.6021 | 1.1043 | 1.0509 |
| No log | 4.6415 | 246 | 1.1143 | 0.6156 | 1.1143 | 1.0556 |
| No log | 4.6792 | 248 | 1.1627 | 0.6117 | 1.1627 | 1.0783 |
| No log | 4.7170 | 250 | 1.1077 | 0.6282 | 1.1077 | 1.0525 |
| No log | 4.7547 | 252 | 0.9599 | 0.6420 | 0.9599 | 0.9798 |
| No log | 4.7925 | 254 | 0.9456 | 0.6354 | 0.9456 | 0.9724 |
| No log | 4.8302 | 256 | 0.9622 | 0.6325 | 0.9622 | 0.9809 |
| No log | 4.8679 | 258 | 0.9747 | 0.6311 | 0.9747 | 0.9873 |
| No log | 4.9057 | 260 | 0.9551 | 0.6542 | 0.9551 | 0.9773 |
| No log | 4.9434 | 262 | 0.9628 | 0.6494 | 0.9628 | 0.9812 |
| No log | 4.9811 | 264 | 0.9077 | 0.6750 | 0.9077 | 0.9527 |
| No log | 5.0189 | 266 | 0.8162 | 0.6979 | 0.8162 | 0.9034 |
| No log | 5.0566 | 268 | 0.7856 | 0.7188 | 0.7856 | 0.8864 |
| No log | 5.0943 | 270 | 0.7929 | 0.7185 | 0.7929 | 0.8905 |
| No log | 5.1321 | 272 | 0.7909 | 0.7230 | 0.7909 | 0.8893 |
| No log | 5.1698 | 274 | 0.7891 | 0.7230 | 0.7891 | 0.8883 |
| No log | 5.2075 | 276 | 0.9092 | 0.6664 | 0.9092 | 0.9535 |
| No log | 5.2453 | 278 | 1.1309 | 0.6119 | 1.1309 | 1.0634 |
| No log | 5.2830 | 280 | 1.3046 | 0.5474 | 1.3046 | 1.1422 |
| No log | 5.3208 | 282 | 1.3028 | 0.5450 | 1.3028 | 1.1414 |
| No log | 5.3585 | 284 | 1.1974 | 0.5572 | 1.1974 | 1.0942 |
| No log | 5.3962 | 286 | 1.1515 | 0.5920 | 1.1515 | 1.0731 |
| No log | 5.4340 | 288 | 1.1281 | 0.6068 | 1.1281 | 1.0621 |
| No log | 5.4717 | 290 | 1.0400 | 0.6423 | 1.0400 | 1.0198 |
| No log | 5.5094 | 292 | 1.0145 | 0.6439 | 1.0145 | 1.0072 |
| No log | 5.5472 | 294 | 1.0870 | 0.6165 | 1.0870 | 1.0426 |
| No log | 5.5849 | 296 | 1.1369 | 0.6020 | 1.1369 | 1.0663 |
| No log | 5.6226 | 298 | 1.1465 | 0.6070 | 1.1465 | 1.0708 |
| No log | 5.6604 | 300 | 1.0489 | 0.6227 | 1.0489 | 1.0241 |
| No log | 5.6981 | 302 | 0.9819 | 0.6402 | 0.9819 | 0.9909 |
| No log | 5.7358 | 304 | 0.8912 | 0.6421 | 0.8912 | 0.9440 |
| No log | 5.7736 | 306 | 0.8125 | 0.6855 | 0.8125 | 0.9014 |
| No log | 5.8113 | 308 | 0.7798 | 0.6901 | 0.7798 | 0.8831 |
| No log | 5.8491 | 310 | 0.8221 | 0.6855 | 0.8221 | 0.9067 |
| No log | 5.8868 | 312 | 0.9553 | 0.6426 | 0.9553 | 0.9774 |
| No log | 5.9245 | 314 | 1.0468 | 0.6521 | 1.0468 | 1.0231 |
| No log | 5.9623 | 316 | 1.2033 | 0.6069 | 1.2033 | 1.0970 |
| No log | 6.0 | 318 | 1.2379 | 0.6099 | 1.2379 | 1.1126 |
| No log | 6.0377 | 320 | 1.1231 | 0.6483 | 1.1231 | 1.0597 |
| No log | 6.0755 | 322 | 0.9791 | 0.6465 | 0.9791 | 0.9895 |
| No log | 6.1132 | 324 | 0.9652 | 0.6407 | 0.9652 | 0.9825 |
| No log | 6.1509 | 326 | 0.9969 | 0.6421 | 0.9969 | 0.9985 |
| No log | 6.1887 | 328 | 1.0851 | 0.6289 | 1.0851 | 1.0417 |
| No log | 6.2264 | 330 | 1.2661 | 0.5740 | 1.2661 | 1.1252 |
| No log | 6.2642 | 332 | 1.3493 | 0.5788 | 1.3493 | 1.1616 |
| No log | 6.3019 | 334 | 1.3108 | 0.5891 | 1.3108 | 1.1449 |
| No log | 6.3396 | 336 | 1.2786 | 0.6069 | 1.2786 | 1.1307 |
| No log | 6.3774 | 338 | 1.2402 | 0.6312 | 1.2402 | 1.1137 |
| No log | 6.4151 | 340 | 1.2126 | 0.6405 | 1.2126 | 1.1012 |
| No log | 6.4528 | 342 | 1.1422 | 0.6216 | 1.1422 | 1.0687 |
| No log | 6.4906 | 344 | 1.0867 | 0.6347 | 1.0867 | 1.0425 |
| No log | 6.5283 | 346 | 1.0849 | 0.6347 | 1.0849 | 1.0416 |
| No log | 6.5660 | 348 | 1.1469 | 0.6216 | 1.1469 | 1.0709 |
| No log | 6.6038 | 350 | 1.1743 | 0.6257 | 1.1743 | 1.0837 |
| No log | 6.6415 | 352 | 1.2732 | 0.6193 | 1.2732 | 1.1284 |
| No log | 6.6792 | 354 | 1.3039 | 0.6141 | 1.3039 | 1.1419 |
| No log | 6.7170 | 356 | 1.2584 | 0.6217 | 1.2584 | 1.1218 |
| No log | 6.7547 | 358 | 1.1287 | 0.6372 | 1.1287 | 1.0624 |
| No log | 6.7925 | 360 | 1.0788 | 0.6360 | 1.0788 | 1.0387 |
| No log | 6.8302 | 362 | 1.1101 | 0.6360 | 1.1101 | 1.0536 |
| No log | 6.8679 | 364 | 1.1223 | 0.6360 | 1.1223 | 1.0594 |
| No log | 6.9057 | 366 | 1.1398 | 0.6359 | 1.1398 | 1.0676 |
| No log | 6.9434 | 368 | 1.1380 | 0.6441 | 1.1380 | 1.0668 |
| No log | 6.9811 | 370 | 1.1775 | 0.6463 | 1.1775 | 1.0851 |
| No log | 7.0189 | 372 | 1.1591 | 0.6371 | 1.1591 | 1.0766 |
| No log | 7.0566 | 374 | 1.0927 | 0.6407 | 1.0927 | 1.0453 |
| No log | 7.0943 | 376 | 1.0565 | 0.6407 | 1.0565 | 1.0279 |
| No log | 7.1321 | 378 | 1.0063 | 0.6462 | 1.0063 | 1.0031 |
| No log | 7.1698 | 380 | 0.9401 | 0.6521 | 0.9401 | 0.9696 |
| No log | 7.2075 | 382 | 0.9284 | 0.6521 | 0.9284 | 0.9635 |
| No log | 7.2453 | 384 | 0.9931 | 0.6567 | 0.9931 | 0.9965 |
| No log | 7.2830 | 386 | 1.1256 | 0.6386 | 1.1256 | 1.0609 |
| No log | 7.3208 | 388 | 1.2384 | 0.5922 | 1.2384 | 1.1128 |
| No log | 7.3585 | 390 | 1.2606 | 0.5861 | 1.2606 | 1.1228 |
| No log | 7.3962 | 392 | 1.1923 | 0.6186 | 1.1923 | 1.0919 |
| No log | 7.4340 | 394 | 1.0572 | 0.6536 | 1.0572 | 1.0282 |
| No log | 7.4717 | 396 | 0.9688 | 0.6591 | 0.9688 | 0.9843 |
| No log | 7.5094 | 398 | 0.9319 | 0.6682 | 0.9319 | 0.9654 |
| No log | 7.5472 | 400 | 0.9469 | 0.6682 | 0.9469 | 0.9731 |
| No log | 7.5849 | 402 | 1.0219 | 0.6541 | 1.0219 | 1.0109 |
| No log | 7.6226 | 404 | 1.1193 | 0.6206 | 1.1193 | 1.0580 |
| No log | 7.6604 | 406 | 1.1752 | 0.6092 | 1.1752 | 1.0840 |
| No log | 7.6981 | 408 | 1.1942 | 0.6092 | 1.1942 | 1.0928 |
| No log | 7.7358 | 410 | 1.1420 | 0.6092 | 1.1420 | 1.0687 |
| No log | 7.7736 | 412 | 1.0544 | 0.6431 | 1.0544 | 1.0268 |
| No log | 7.8113 | 414 | 0.9450 | 0.6604 | 0.9450 | 0.9721 |
| No log | 7.8491 | 416 | 0.8726 | 0.6575 | 0.8726 | 0.9341 |
| No log | 7.8868 | 418 | 0.8418 | 0.7028 | 0.8418 | 0.9175 |
| No log | 7.9245 | 420 | 0.8497 | 0.6928 | 0.8497 | 0.9218 |
| No log | 7.9623 | 422 | 0.8883 | 0.6786 | 0.8883 | 0.9425 |
| No log | 8.0 | 424 | 0.9579 | 0.6557 | 0.9579 | 0.9787 |
| No log | 8.0377 | 426 | 1.0281 | 0.6423 | 1.0281 | 1.0140 |
| No log | 8.0755 | 428 | 1.0769 | 0.6398 | 1.0769 | 1.0377 |
| No log | 8.1132 | 430 | 1.1056 | 0.6326 | 1.1056 | 1.0515 |
| No log | 8.1509 | 432 | 1.0829 | 0.6339 | 1.0829 | 1.0406 |
| No log | 8.1887 | 434 | 1.0150 | 0.6541 | 1.0150 | 1.0075 |
| No log | 8.2264 | 436 | 0.9220 | 0.6656 | 0.9220 | 0.9602 |
| No log | 8.2642 | 438 | 0.8546 | 0.6909 | 0.8546 | 0.9244 |
| No log | 8.3019 | 440 | 0.8279 | 0.6936 | 0.8279 | 0.9099 |
| No log | 8.3396 | 442 | 0.8367 | 0.6972 | 0.8367 | 0.9147 |
| No log | 8.3774 | 444 | 0.8689 | 0.6909 | 0.8689 | 0.9321 |
| No log | 8.4151 | 446 | 0.9105 | 0.6656 | 0.9105 | 0.9542 |
| No log | 8.4528 | 448 | 0.9811 | 0.6559 | 0.9811 | 0.9905 |
| No log | 8.4906 | 450 | 1.0369 | 0.6488 | 1.0369 | 1.0183 |
| No log | 8.5283 | 452 | 1.0752 | 0.6447 | 1.0752 | 1.0369 |
| No log | 8.5660 | 454 | 1.1171 | 0.6274 | 1.1171 | 1.0569 |
| No log | 8.6038 | 456 | 1.1557 | 0.6318 | 1.1557 | 1.0750 |
| No log | 8.6415 | 458 | 1.1620 | 0.6209 | 1.1620 | 1.0780 |
| No log | 8.6792 | 460 | 1.1295 | 0.6247 | 1.1295 | 1.0628 |
| No log | 8.7170 | 462 | 1.0845 | 0.6274 | 1.0845 | 1.0414 |
| No log | 8.7547 | 464 | 1.0626 | 0.6328 | 1.0626 | 1.0308 |
| No log | 8.7925 | 466 | 1.0572 | 0.6328 | 1.0572 | 1.0282 |
| No log | 8.8302 | 468 | 1.0703 | 0.6328 | 1.0703 | 1.0345 |
| No log | 8.8679 | 470 | 1.0757 | 0.6328 | 1.0757 | 1.0372 |
| No log | 8.9057 | 472 | 1.0835 | 0.6328 | 1.0835 | 1.0409 |
| No log | 8.9434 | 474 | 1.0962 | 0.6412 | 1.0962 | 1.0470 |
| No log | 8.9811 | 476 | 1.0882 | 0.6412 | 1.0882 | 1.0432 |
| No log | 9.0189 | 478 | 1.0771 | 0.6412 | 1.0771 | 1.0378 |
| No log | 9.0566 | 480 | 1.0562 | 0.6328 | 1.0562 | 1.0277 |
| No log | 9.0943 | 482 | 1.0646 | 0.6328 | 1.0646 | 1.0318 |
| No log | 9.1321 | 484 | 1.0663 | 0.6389 | 1.0663 | 1.0326 |
| No log | 9.1698 | 486 | 1.0779 | 0.6389 | 1.0779 | 1.0382 |
| No log | 9.2075 | 488 | 1.1029 | 0.6328 | 1.1029 | 1.0502 |
| No log | 9.2453 | 490 | 1.1087 | 0.6229 | 1.1087 | 1.0529 |
| No log | 9.2830 | 492 | 1.1015 | 0.6287 | 1.1015 | 1.0495 |
| No log | 9.3208 | 494 | 1.0933 | 0.6447 | 1.0933 | 1.0456 |
| No log | 9.3585 | 496 | 1.0700 | 0.6551 | 1.0700 | 1.0344 |
| No log | 9.3962 | 498 | 1.0608 | 0.6551 | 1.0608 | 1.0299 |
| 0.3535 | 9.4340 | 500 | 1.0556 | 0.6551 | 1.0556 | 1.0274 |
| 0.3535 | 9.4717 | 502 | 1.0509 | 0.6551 | 1.0509 | 1.0251 |
| 0.3535 | 9.5094 | 504 | 1.0565 | 0.6462 | 1.0565 | 1.0279 |
| 0.3535 | 9.5472 | 506 | 1.0652 | 0.6462 | 1.0652 | 1.0321 |
| 0.3535 | 9.5849 | 508 | 1.0657 | 0.6462 | 1.0657 | 1.0323 |
| 0.3535 | 9.6226 | 510 | 1.0595 | 0.6462 | 1.0595 | 1.0293 |
| 0.3535 | 9.6604 | 512 | 1.0536 | 0.6462 | 1.0536 | 1.0264 |
| 0.3535 | 9.6981 | 514 | 1.0486 | 0.6462 | 1.0486 | 1.0240 |
| 0.3535 | 9.7358 | 516 | 1.0421 | 0.6462 | 1.0421 | 1.0208 |
| 0.3535 | 9.7736 | 518 | 1.0379 | 0.6462 | 1.0379 | 1.0188 |
| 0.3535 | 9.8113 | 520 | 1.0359 | 0.6462 | 1.0359 | 1.0178 |
| 0.3535 | 9.8491 | 522 | 1.0363 | 0.6462 | 1.0363 | 1.0180 |
| 0.3535 | 9.8868 | 524 | 1.0350 | 0.6462 | 1.0350 | 1.0174 |
| 0.3535 | 9.9245 | 526 | 1.0325 | 0.6462 | 1.0325 | 1.0161 |
| 0.3535 | 9.9623 | 528 | 1.0314 | 0.6462 | 1.0314 | 1.0156 |
| 0.3535 | 10.0 | 530 | 1.0305 | 0.6551 | 1.0305 | 1.0151 |
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/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k16_task5_organization
Base model
aubmindlab/bert-base-arabertv02