Instructions to use MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k10_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_k10_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_k10_task3_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k10_task3_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k10_task3_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k10_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: 0.7247
- Qwk: 0.2464
- Mse: 0.7247
- Rmse: 0.8513
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 | 0.0444 | 2 | 3.2300 | -0.0149 | 3.2300 | 1.7972 |
| No log | 0.0889 | 4 | 1.6866 | -0.0070 | 1.6866 | 1.2987 |
| No log | 0.1333 | 6 | 1.4718 | 0.0255 | 1.4718 | 1.2132 |
| No log | 0.1778 | 8 | 0.8949 | 0.1673 | 0.8949 | 0.9460 |
| No log | 0.2222 | 10 | 0.5655 | 0.0222 | 0.5655 | 0.7520 |
| No log | 0.2667 | 12 | 0.5613 | 0.0569 | 0.5613 | 0.7492 |
| No log | 0.3111 | 14 | 0.5551 | 0.0303 | 0.5551 | 0.7451 |
| No log | 0.3556 | 16 | 0.5454 | 0.0569 | 0.5454 | 0.7385 |
| No log | 0.4 | 18 | 0.5520 | -0.0159 | 0.5520 | 0.7430 |
| No log | 0.4444 | 20 | 0.8311 | 0.2000 | 0.8311 | 0.9116 |
| No log | 0.4889 | 22 | 0.7803 | 0.2300 | 0.7803 | 0.8834 |
| No log | 0.5333 | 24 | 0.6153 | 0.0720 | 0.6153 | 0.7844 |
| No log | 0.5778 | 26 | 0.7098 | 0.2000 | 0.7098 | 0.8425 |
| No log | 0.6222 | 28 | 0.6655 | 0.1888 | 0.6655 | 0.8158 |
| No log | 0.6667 | 30 | 0.6458 | -0.1007 | 0.6458 | 0.8036 |
| No log | 0.7111 | 32 | 0.7409 | 0.0345 | 0.7409 | 0.8607 |
| No log | 0.7556 | 34 | 0.6909 | -0.0390 | 0.6909 | 0.8312 |
| No log | 0.8 | 36 | 0.6797 | -0.0072 | 0.6797 | 0.8244 |
| No log | 0.8444 | 38 | 0.6871 | 0.0199 | 0.6871 | 0.8289 |
| No log | 0.8889 | 40 | 0.7641 | 0.0311 | 0.7641 | 0.8741 |
| No log | 0.9333 | 42 | 0.9004 | -0.0275 | 0.9004 | 0.9489 |
| No log | 0.9778 | 44 | 0.7186 | 0.1628 | 0.7186 | 0.8477 |
| No log | 1.0222 | 46 | 0.7551 | 0.0737 | 0.7551 | 0.8690 |
| No log | 1.0667 | 48 | 0.6982 | 0.1373 | 0.6982 | 0.8356 |
| No log | 1.1111 | 50 | 0.7325 | 0.0728 | 0.7325 | 0.8559 |
| No log | 1.1556 | 52 | 1.0763 | -0.0154 | 1.0763 | 1.0374 |
| No log | 1.2 | 54 | 0.7183 | 0.0769 | 0.7183 | 0.8476 |
| No log | 1.2444 | 56 | 0.6764 | 0.1345 | 0.6764 | 0.8224 |
| No log | 1.2889 | 58 | 0.7061 | 0.0617 | 0.7061 | 0.8403 |
| No log | 1.3333 | 60 | 1.0978 | -0.0277 | 1.0978 | 1.0478 |
| No log | 1.3778 | 62 | 1.0735 | 0.0252 | 1.0735 | 1.0361 |
| No log | 1.4222 | 64 | 0.8700 | 0.0891 | 0.8700 | 0.9328 |
| No log | 1.4667 | 66 | 0.8345 | 0.0891 | 0.8345 | 0.9135 |
| No log | 1.5111 | 68 | 0.7870 | 0.0802 | 0.7870 | 0.8871 |
| No log | 1.5556 | 70 | 1.0944 | 0.0 | 1.0944 | 1.0461 |
| No log | 1.6 | 72 | 1.0873 | 0.0038 | 1.0873 | 1.0427 |
| No log | 1.6444 | 74 | 1.0292 | 0.0169 | 1.0292 | 1.0145 |
| No log | 1.6889 | 76 | 1.2860 | 0.0270 | 1.2860 | 1.1340 |
| No log | 1.7333 | 78 | 0.9786 | 0.0717 | 0.9786 | 0.9892 |
| No log | 1.7778 | 80 | 0.7560 | 0.2577 | 0.7560 | 0.8695 |
| No log | 1.8222 | 82 | 0.8102 | 0.2153 | 0.8102 | 0.9001 |
| No log | 1.8667 | 84 | 1.4464 | 0.0464 | 1.4464 | 1.2027 |
| No log | 1.9111 | 86 | 1.4895 | 0.0502 | 1.4895 | 1.2205 |
| No log | 1.9556 | 88 | 1.2051 | 0.0262 | 1.2051 | 1.0977 |
| No log | 2.0 | 90 | 0.9645 | 0.0308 | 0.9645 | 0.9821 |
| No log | 2.0444 | 92 | 0.7751 | 0.2727 | 0.7751 | 0.8804 |
| No log | 2.0889 | 94 | 0.8084 | 0.2444 | 0.8084 | 0.8991 |
| No log | 2.1333 | 96 | 0.9621 | 0.0539 | 0.9621 | 0.9809 |
| No log | 2.1778 | 98 | 1.6207 | 0.1111 | 1.6207 | 1.2731 |
| No log | 2.2222 | 100 | 1.3510 | 0.1169 | 1.3510 | 1.1623 |
| No log | 2.2667 | 102 | 0.8183 | 0.1538 | 0.8183 | 0.9046 |
| No log | 2.3111 | 104 | 0.8754 | 0.2146 | 0.8754 | 0.9356 |
| No log | 2.3556 | 106 | 0.9240 | 0.2489 | 0.9240 | 0.9613 |
| No log | 2.4 | 108 | 0.9545 | 0.2208 | 0.9545 | 0.9770 |
| No log | 2.4444 | 110 | 1.3324 | 0.0789 | 1.3324 | 1.1543 |
| No log | 2.4889 | 112 | 0.8852 | 0.1269 | 0.8852 | 0.9408 |
| No log | 2.5333 | 114 | 0.7701 | 0.1919 | 0.7701 | 0.8775 |
| No log | 2.5778 | 116 | 0.8001 | 0.2315 | 0.8001 | 0.8945 |
| No log | 2.6222 | 118 | 0.7511 | 0.2350 | 0.7511 | 0.8666 |
| No log | 2.6667 | 120 | 0.8243 | 0.1600 | 0.8243 | 0.9079 |
| No log | 2.7111 | 122 | 1.1652 | 0.0312 | 1.1652 | 1.0795 |
| No log | 2.7556 | 124 | 1.1735 | 0.0111 | 1.1735 | 1.0833 |
| No log | 2.8 | 126 | 0.7277 | 0.2513 | 0.7277 | 0.8530 |
| No log | 2.8444 | 128 | 0.7175 | 0.2626 | 0.7175 | 0.8470 |
| No log | 2.8889 | 130 | 0.7618 | 0.2000 | 0.7618 | 0.8728 |
| No log | 2.9333 | 132 | 0.8249 | 0.1269 | 0.8249 | 0.9082 |
| No log | 2.9778 | 134 | 1.0374 | -0.0164 | 1.0374 | 1.0186 |
| No log | 3.0222 | 136 | 1.0806 | -0.0164 | 1.0806 | 1.0395 |
| No log | 3.0667 | 138 | 0.7984 | 0.1086 | 0.7984 | 0.8935 |
| No log | 3.1111 | 140 | 0.8269 | 0.0512 | 0.8269 | 0.9094 |
| No log | 3.1556 | 142 | 0.7617 | 0.2889 | 0.7617 | 0.8728 |
| No log | 3.2 | 144 | 1.1631 | 0.0840 | 1.1631 | 1.0785 |
| No log | 3.2444 | 146 | 1.8137 | 0.0787 | 1.8137 | 1.3468 |
| No log | 3.2889 | 148 | 1.3948 | 0.1325 | 1.3948 | 1.1810 |
| No log | 3.3333 | 150 | 0.6668 | 0.1910 | 0.6668 | 0.8166 |
| No log | 3.3778 | 152 | 0.6601 | 0.2393 | 0.6601 | 0.8125 |
| No log | 3.4222 | 154 | 0.6507 | 0.2749 | 0.6507 | 0.8067 |
| No log | 3.4667 | 156 | 0.6683 | 0.2258 | 0.6683 | 0.8175 |
| No log | 3.5111 | 158 | 0.7365 | 0.1568 | 0.7365 | 0.8582 |
| No log | 3.5556 | 160 | 0.7321 | 0.2653 | 0.7321 | 0.8557 |
| No log | 3.6 | 162 | 0.7172 | 0.2990 | 0.7172 | 0.8469 |
| No log | 3.6444 | 164 | 0.7421 | 0.1628 | 0.7421 | 0.8614 |
| No log | 3.6889 | 166 | 0.7474 | 0.2965 | 0.7474 | 0.8645 |
| No log | 3.7333 | 168 | 0.9134 | 0.1781 | 0.9134 | 0.9557 |
| No log | 3.7778 | 170 | 0.9228 | 0.1786 | 0.9228 | 0.9606 |
| No log | 3.8222 | 172 | 0.7121 | 0.2245 | 0.7121 | 0.8439 |
| No log | 3.8667 | 174 | 0.8061 | 0.2676 | 0.8061 | 0.8978 |
| No log | 3.9111 | 176 | 0.8893 | 0.1336 | 0.8893 | 0.9430 |
| No log | 3.9556 | 178 | 0.6875 | 0.2787 | 0.6875 | 0.8291 |
| No log | 4.0 | 180 | 0.8988 | 0.1453 | 0.8988 | 0.9481 |
| No log | 4.0444 | 182 | 1.2635 | 0.1409 | 1.2635 | 1.1241 |
| No log | 4.0889 | 184 | 1.0170 | 0.1008 | 1.0170 | 1.0085 |
| No log | 4.1333 | 186 | 0.6653 | 0.2298 | 0.6653 | 0.8157 |
| No log | 4.1778 | 188 | 0.7602 | 0.1357 | 0.7602 | 0.8719 |
| No log | 4.2222 | 190 | 0.7576 | 0.1841 | 0.7576 | 0.8704 |
| No log | 4.2667 | 192 | 0.6715 | 0.3136 | 0.6715 | 0.8194 |
| No log | 4.3111 | 194 | 0.8296 | 0.0714 | 0.8296 | 0.9108 |
| No log | 4.3556 | 196 | 1.0359 | 0.0949 | 1.0359 | 1.0178 |
| No log | 4.4 | 198 | 0.8830 | 0.1392 | 0.8830 | 0.9397 |
| No log | 4.4444 | 200 | 0.8187 | 0.1273 | 0.8187 | 0.9048 |
| No log | 4.4889 | 202 | 0.7186 | 0.2653 | 0.7186 | 0.8477 |
| No log | 4.5333 | 204 | 0.7372 | 0.2323 | 0.7372 | 0.8586 |
| No log | 4.5778 | 206 | 0.8521 | 0.1660 | 0.8521 | 0.9231 |
| No log | 4.6222 | 208 | 0.8257 | 0.1628 | 0.8257 | 0.9087 |
| No log | 4.6667 | 210 | 0.7021 | 0.2340 | 0.7021 | 0.8379 |
| No log | 4.7111 | 212 | 0.6850 | 0.3061 | 0.6850 | 0.8276 |
| No log | 4.7556 | 214 | 0.6150 | 0.3520 | 0.6150 | 0.7842 |
| No log | 4.8 | 216 | 0.6979 | 0.2165 | 0.6979 | 0.8354 |
| No log | 4.8444 | 218 | 0.6583 | 0.2487 | 0.6583 | 0.8114 |
| No log | 4.8889 | 220 | 0.6039 | 0.2865 | 0.6039 | 0.7771 |
| No log | 4.9333 | 222 | 0.5460 | 0.3797 | 0.5460 | 0.7389 |
| No log | 4.9778 | 224 | 0.5540 | 0.3913 | 0.5540 | 0.7443 |
| No log | 5.0222 | 226 | 0.5711 | 0.4105 | 0.5711 | 0.7557 |
| No log | 5.0667 | 228 | 0.6204 | 0.3641 | 0.6204 | 0.7876 |
| No log | 5.1111 | 230 | 0.6388 | 0.3641 | 0.6388 | 0.7993 |
| No log | 5.1556 | 232 | 0.6900 | 0.2963 | 0.6900 | 0.8306 |
| No log | 5.2 | 234 | 0.9107 | 0.2000 | 0.9107 | 0.9543 |
| No log | 5.2444 | 236 | 1.0195 | 0.1506 | 1.0195 | 1.0097 |
| No log | 5.2889 | 238 | 0.8362 | 0.2348 | 0.8362 | 0.9144 |
| No log | 5.3333 | 240 | 0.6980 | 0.3548 | 0.6980 | 0.8355 |
| No log | 5.3778 | 242 | 0.7505 | 0.2287 | 0.7505 | 0.8663 |
| No log | 5.4222 | 244 | 0.6969 | 0.3469 | 0.6969 | 0.8348 |
| No log | 5.4667 | 246 | 0.7223 | 0.1919 | 0.7223 | 0.8499 |
| No log | 5.5111 | 248 | 0.6953 | 0.2239 | 0.6953 | 0.8338 |
| No log | 5.5556 | 250 | 0.6827 | 0.3927 | 0.6827 | 0.8263 |
| No log | 5.6 | 252 | 0.8056 | 0.2356 | 0.8056 | 0.8975 |
| No log | 5.6444 | 254 | 0.8449 | 0.2208 | 0.8449 | 0.9192 |
| No log | 5.6889 | 256 | 0.7297 | 0.2963 | 0.7297 | 0.8543 |
| No log | 5.7333 | 258 | 0.8200 | 0.1628 | 0.8200 | 0.9055 |
| No log | 5.7778 | 260 | 0.9761 | 0.1169 | 0.9761 | 0.9880 |
| No log | 5.8222 | 262 | 0.8589 | 0.1776 | 0.8589 | 0.9268 |
| No log | 5.8667 | 264 | 0.7384 | 0.2233 | 0.7384 | 0.8593 |
| No log | 5.9111 | 266 | 0.6952 | 0.2842 | 0.6952 | 0.8338 |
| No log | 5.9556 | 268 | 0.6817 | 0.2917 | 0.6817 | 0.8257 |
| No log | 6.0 | 270 | 0.6975 | 0.1917 | 0.6975 | 0.8351 |
| No log | 6.0444 | 272 | 0.7122 | 0.1753 | 0.7122 | 0.8439 |
| No log | 6.0889 | 274 | 0.6602 | 0.2432 | 0.6602 | 0.8125 |
| No log | 6.1333 | 276 | 0.6205 | 0.2174 | 0.6205 | 0.7877 |
| No log | 6.1778 | 278 | 0.6443 | 0.2340 | 0.6443 | 0.8027 |
| No log | 6.2222 | 280 | 0.7023 | 0.1667 | 0.7023 | 0.8380 |
| No log | 6.2667 | 282 | 0.6546 | 0.2340 | 0.6546 | 0.8091 |
| No log | 6.3111 | 284 | 0.6298 | 0.3407 | 0.6298 | 0.7936 |
| No log | 6.3556 | 286 | 0.6547 | 0.2941 | 0.6547 | 0.8091 |
| No log | 6.4 | 288 | 0.7235 | 0.2157 | 0.7235 | 0.8506 |
| No log | 6.4444 | 290 | 0.7705 | 0.1781 | 0.7705 | 0.8778 |
| No log | 6.4889 | 292 | 0.8232 | 0.1549 | 0.8232 | 0.9073 |
| No log | 6.5333 | 294 | 0.7880 | 0.2432 | 0.7880 | 0.8877 |
| No log | 6.5778 | 296 | 0.7517 | 0.2475 | 0.7517 | 0.8670 |
| No log | 6.6222 | 298 | 0.7688 | 0.1481 | 0.7688 | 0.8768 |
| No log | 6.6667 | 300 | 0.8379 | 0.1238 | 0.8379 | 0.9154 |
| No log | 6.7111 | 302 | 0.7658 | 0.1238 | 0.7658 | 0.8751 |
| No log | 6.7556 | 304 | 0.6817 | 0.2258 | 0.6817 | 0.8257 |
| No log | 6.8 | 306 | 0.6663 | 0.3191 | 0.6663 | 0.8163 |
| No log | 6.8444 | 308 | 0.6710 | 0.2746 | 0.6710 | 0.8191 |
| No log | 6.8889 | 310 | 0.6911 | 0.2917 | 0.6911 | 0.8313 |
| No log | 6.9333 | 312 | 0.7084 | 0.2917 | 0.7084 | 0.8417 |
| No log | 6.9778 | 314 | 0.7125 | 0.2536 | 0.7125 | 0.8441 |
| No log | 7.0222 | 316 | 0.7268 | 0.2536 | 0.7268 | 0.8525 |
| No log | 7.0667 | 318 | 0.7242 | 0.2917 | 0.7242 | 0.8510 |
| No log | 7.1111 | 320 | 0.7237 | 0.2917 | 0.7237 | 0.8507 |
| No log | 7.1556 | 322 | 0.7062 | 0.2917 | 0.7062 | 0.8404 |
| No log | 7.2 | 324 | 0.6829 | 0.2464 | 0.6829 | 0.8264 |
| No log | 7.2444 | 326 | 0.6701 | 0.3299 | 0.6701 | 0.8186 |
| No log | 7.2889 | 328 | 0.6596 | 0.3043 | 0.6596 | 0.8121 |
| No log | 7.3333 | 330 | 0.6604 | 0.2265 | 0.6604 | 0.8127 |
| No log | 7.3778 | 332 | 0.7037 | 0.1556 | 0.7037 | 0.8389 |
| No log | 7.4222 | 334 | 0.7394 | 0.2000 | 0.7394 | 0.8599 |
| No log | 7.4667 | 336 | 0.7042 | 0.1913 | 0.7042 | 0.8392 |
| No log | 7.5111 | 338 | 0.6726 | 0.2727 | 0.6726 | 0.8201 |
| No log | 7.5556 | 340 | 0.7022 | 0.2549 | 0.7022 | 0.8380 |
| No log | 7.6 | 342 | 0.7115 | 0.2549 | 0.7115 | 0.8435 |
| No log | 7.6444 | 344 | 0.6870 | 0.3077 | 0.6870 | 0.8289 |
| No log | 7.6889 | 346 | 0.6967 | 0.28 | 0.6967 | 0.8347 |
| No log | 7.7333 | 348 | 0.7742 | 0.2300 | 0.7742 | 0.8799 |
| No log | 7.7778 | 350 | 0.7984 | 0.1628 | 0.7984 | 0.8935 |
| No log | 7.8222 | 352 | 0.7559 | 0.2593 | 0.7559 | 0.8694 |
| No log | 7.8667 | 354 | 0.7168 | 0.2563 | 0.7168 | 0.8466 |
| No log | 7.9111 | 356 | 0.7116 | 0.2563 | 0.7116 | 0.8436 |
| No log | 7.9556 | 358 | 0.7399 | 0.2986 | 0.7399 | 0.8602 |
| No log | 8.0 | 360 | 0.7685 | 0.1928 | 0.7685 | 0.8767 |
| No log | 8.0444 | 362 | 0.7568 | 0.2676 | 0.7568 | 0.8699 |
| No log | 8.0889 | 364 | 0.7390 | 0.2692 | 0.7390 | 0.8597 |
| No log | 8.1333 | 366 | 0.6942 | 0.2653 | 0.6942 | 0.8332 |
| No log | 8.1778 | 368 | 0.6747 | 0.2549 | 0.6747 | 0.8214 |
| No log | 8.2222 | 370 | 0.6960 | 0.3171 | 0.6960 | 0.8343 |
| No log | 8.2667 | 372 | 0.7018 | 0.2762 | 0.7018 | 0.8377 |
| No log | 8.3111 | 374 | 0.7083 | 0.2390 | 0.7083 | 0.8416 |
| No log | 8.3556 | 376 | 0.7517 | 0.2621 | 0.7517 | 0.8670 |
| No log | 8.4 | 378 | 0.7746 | 0.2212 | 0.7746 | 0.8801 |
| No log | 8.4444 | 380 | 0.7500 | 0.2621 | 0.7500 | 0.8660 |
| No log | 8.4889 | 382 | 0.7369 | 0.2637 | 0.7369 | 0.8584 |
| No log | 8.5333 | 384 | 0.7130 | 0.2464 | 0.7130 | 0.8444 |
| No log | 8.5778 | 386 | 0.7015 | 0.24 | 0.7015 | 0.8376 |
| No log | 8.6222 | 388 | 0.6968 | 0.2549 | 0.6968 | 0.8348 |
| No log | 8.6667 | 390 | 0.6985 | 0.2487 | 0.6985 | 0.8358 |
| No log | 8.7111 | 392 | 0.7214 | 0.2637 | 0.7214 | 0.8493 |
| No log | 8.7556 | 394 | 0.7458 | 0.2637 | 0.7458 | 0.8636 |
| No log | 8.8 | 396 | 0.7353 | 0.2637 | 0.7353 | 0.8575 |
| No log | 8.8444 | 398 | 0.7288 | 0.2323 | 0.7288 | 0.8537 |
| No log | 8.8889 | 400 | 0.7059 | 0.2653 | 0.7059 | 0.8402 |
| No log | 8.9333 | 402 | 0.6947 | 0.2475 | 0.6947 | 0.8335 |
| No log | 8.9778 | 404 | 0.6944 | 0.2475 | 0.6944 | 0.8333 |
| No log | 9.0222 | 406 | 0.6909 | 0.2821 | 0.6909 | 0.8312 |
| No log | 9.0667 | 408 | 0.6961 | 0.2727 | 0.6961 | 0.8344 |
| No log | 9.1111 | 410 | 0.7024 | 0.28 | 0.7024 | 0.8381 |
| No log | 9.1556 | 412 | 0.7146 | 0.2475 | 0.7146 | 0.8453 |
| No log | 9.2 | 414 | 0.7229 | 0.2453 | 0.7229 | 0.8503 |
| No log | 9.2444 | 416 | 0.7357 | 0.2453 | 0.7357 | 0.8578 |
| No log | 9.2889 | 418 | 0.7494 | 0.2986 | 0.7494 | 0.8657 |
| No log | 9.3333 | 420 | 0.7677 | 0.2593 | 0.7677 | 0.8762 |
| No log | 9.3778 | 422 | 0.7626 | 0.2593 | 0.7626 | 0.8733 |
| No log | 9.4222 | 424 | 0.7539 | 0.2593 | 0.7539 | 0.8683 |
| No log | 9.4667 | 426 | 0.7420 | 0.2637 | 0.7420 | 0.8614 |
| No log | 9.5111 | 428 | 0.7383 | 0.2637 | 0.7383 | 0.8592 |
| No log | 9.5556 | 430 | 0.7273 | 0.2453 | 0.7273 | 0.8528 |
| No log | 9.6 | 432 | 0.7204 | 0.2475 | 0.7204 | 0.8488 |
| No log | 9.6444 | 434 | 0.7207 | 0.2475 | 0.7207 | 0.8489 |
| No log | 9.6889 | 436 | 0.7212 | 0.2475 | 0.7212 | 0.8492 |
| No log | 9.7333 | 438 | 0.7213 | 0.2475 | 0.7213 | 0.8493 |
| No log | 9.7778 | 440 | 0.7203 | 0.2475 | 0.7203 | 0.8487 |
| No log | 9.8222 | 442 | 0.7211 | 0.2475 | 0.7211 | 0.8492 |
| No log | 9.8667 | 444 | 0.7223 | 0.2475 | 0.7223 | 0.8499 |
| No log | 9.9111 | 446 | 0.7235 | 0.2464 | 0.7235 | 0.8506 |
| No log | 9.9556 | 448 | 0.7245 | 0.2464 | 0.7245 | 0.8512 |
| No log | 10.0 | 450 | 0.7247 | 0.2464 | 0.7247 | 0.8513 |
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_k10_task3_organization
Base model
aubmindlab/bert-base-arabertv02