Instructions to use MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k8_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_k8_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_k8_task3_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k8_task3_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k8_task3_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k8_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: 0.6944
- Qwk: 0.2308
- Mse: 0.6944
- Rmse: 0.8333
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 | 0.0476 | 2 | 3.0789 | 0.0 | 3.0789 | 1.7547 |
| No log | 0.0952 | 4 | 1.7285 | 0.0255 | 1.7285 | 1.3147 |
| No log | 0.1429 | 6 | 1.0475 | 0.0345 | 1.0475 | 1.0235 |
| No log | 0.1905 | 8 | 0.6160 | 0.0725 | 0.6160 | 0.7848 |
| No log | 0.2381 | 10 | 0.5767 | 0.0 | 0.5767 | 0.7594 |
| No log | 0.2857 | 12 | 0.5785 | 0.0 | 0.5785 | 0.7606 |
| No log | 0.3333 | 14 | 0.6612 | 0.2533 | 0.6612 | 0.8132 |
| No log | 0.3810 | 16 | 0.9947 | 0.0431 | 0.9947 | 0.9974 |
| No log | 0.4286 | 18 | 1.1697 | 0.0 | 1.1697 | 1.0815 |
| No log | 0.4762 | 20 | 0.8379 | 0.0877 | 0.8379 | 0.9154 |
| No log | 0.5238 | 22 | 0.6558 | 0.1638 | 0.6558 | 0.8098 |
| No log | 0.5714 | 24 | 0.5606 | 0.0 | 0.5606 | 0.7487 |
| No log | 0.6190 | 26 | 0.7412 | 0.1407 | 0.7412 | 0.8609 |
| No log | 0.6667 | 28 | 0.8557 | 0.1500 | 0.8557 | 0.9251 |
| No log | 0.7143 | 30 | 0.9847 | 0.0298 | 0.9847 | 0.9923 |
| No log | 0.7619 | 32 | 0.8291 | -0.0612 | 0.8291 | 0.9105 |
| No log | 0.8095 | 34 | 0.8142 | -0.1579 | 0.8142 | 0.9024 |
| No log | 0.8571 | 36 | 0.8298 | -0.0481 | 0.8298 | 0.9109 |
| No log | 0.9048 | 38 | 0.7771 | 0.0995 | 0.7771 | 0.8815 |
| No log | 0.9524 | 40 | 1.0711 | 0.0216 | 1.0711 | 1.0349 |
| No log | 1.0 | 42 | 1.1293 | -0.0207 | 1.1293 | 1.0627 |
| No log | 1.0476 | 44 | 0.7781 | 0.1045 | 0.7781 | 0.8821 |
| No log | 1.0952 | 46 | 0.6819 | 0.1138 | 0.6819 | 0.8258 |
| No log | 1.1429 | 48 | 0.6876 | 0.1083 | 0.6876 | 0.8292 |
| No log | 1.1905 | 50 | 0.7337 | 0.0899 | 0.7337 | 0.8565 |
| No log | 1.2381 | 52 | 0.6116 | 0.1899 | 0.6116 | 0.7820 |
| No log | 1.2857 | 54 | 0.6019 | 0.2393 | 0.6019 | 0.7758 |
| No log | 1.3333 | 56 | 0.5627 | 0.1329 | 0.5627 | 0.7501 |
| No log | 1.3810 | 58 | 1.3288 | 0.0984 | 1.3288 | 1.1527 |
| No log | 1.4286 | 60 | 1.7828 | 0.0090 | 1.7828 | 1.3352 |
| No log | 1.4762 | 62 | 1.3491 | 0.0984 | 1.3491 | 1.1615 |
| No log | 1.5238 | 64 | 0.6897 | 0.1908 | 0.6897 | 0.8305 |
| No log | 1.5714 | 66 | 0.5420 | 0.3333 | 0.5420 | 0.7362 |
| No log | 1.6190 | 68 | 0.8748 | 0.2134 | 0.8748 | 0.9353 |
| No log | 1.6667 | 70 | 0.7404 | 0.2920 | 0.7404 | 0.8605 |
| No log | 1.7143 | 72 | 0.5347 | 0.0897 | 0.5347 | 0.7312 |
| No log | 1.7619 | 74 | 0.8327 | 0.2661 | 0.8327 | 0.9125 |
| No log | 1.8095 | 76 | 0.8493 | 0.2281 | 0.8493 | 0.9216 |
| No log | 1.8571 | 78 | 0.5722 | 0.1020 | 0.5722 | 0.7565 |
| No log | 1.9048 | 80 | 0.6284 | 0.2179 | 0.6284 | 0.7927 |
| No log | 1.9524 | 82 | 0.6921 | 0.1915 | 0.6921 | 0.8319 |
| No log | 2.0 | 84 | 0.6001 | 0.4091 | 0.6001 | 0.7747 |
| No log | 2.0476 | 86 | 0.6606 | 0.1917 | 0.6606 | 0.8127 |
| No log | 2.0952 | 88 | 0.6387 | 0.3089 | 0.6387 | 0.7992 |
| No log | 2.1429 | 90 | 0.6372 | 0.3548 | 0.6372 | 0.7983 |
| No log | 2.1905 | 92 | 0.7912 | 0.2775 | 0.7912 | 0.8895 |
| No log | 2.2381 | 94 | 0.8104 | 0.2838 | 0.8104 | 0.9002 |
| No log | 2.2857 | 96 | 0.6144 | 0.2000 | 0.6144 | 0.7838 |
| No log | 2.3333 | 98 | 0.5975 | 0.2444 | 0.5975 | 0.7730 |
| No log | 2.3810 | 100 | 0.6406 | 0.3118 | 0.6406 | 0.8004 |
| No log | 2.4286 | 102 | 0.8200 | 0.2900 | 0.8200 | 0.9055 |
| No log | 2.4762 | 104 | 1.1003 | 0.2440 | 1.1003 | 1.0490 |
| No log | 2.5238 | 106 | 0.9204 | 0.2593 | 0.9204 | 0.9593 |
| No log | 2.5714 | 108 | 0.6661 | 0.3052 | 0.6661 | 0.8161 |
| No log | 2.6190 | 110 | 0.6821 | 0.2153 | 0.6821 | 0.8259 |
| No log | 2.6667 | 112 | 0.6275 | 0.2709 | 0.6275 | 0.7922 |
| No log | 2.7143 | 114 | 0.8611 | 0.3080 | 0.8611 | 0.9280 |
| No log | 2.7619 | 116 | 1.0425 | 0.2778 | 1.0425 | 1.0210 |
| No log | 2.8095 | 118 | 0.7608 | 0.2333 | 0.7608 | 0.8723 |
| No log | 2.8571 | 120 | 0.7249 | 0.2605 | 0.7249 | 0.8514 |
| No log | 2.9048 | 122 | 0.7989 | 0.2140 | 0.7989 | 0.8938 |
| No log | 2.9524 | 124 | 0.9665 | 0.2239 | 0.9665 | 0.9831 |
| No log | 3.0 | 126 | 1.0858 | 0.25 | 1.0858 | 1.0420 |
| No log | 3.0476 | 128 | 0.7594 | 0.2212 | 0.7594 | 0.8715 |
| No log | 3.0952 | 130 | 0.7037 | 0.3251 | 0.7037 | 0.8388 |
| No log | 3.1429 | 132 | 0.8101 | 0.2397 | 0.8101 | 0.9001 |
| No log | 3.1905 | 134 | 0.6651 | 0.3628 | 0.6651 | 0.8156 |
| No log | 3.2381 | 136 | 0.8809 | 0.2414 | 0.8809 | 0.9386 |
| No log | 3.2857 | 138 | 1.0623 | 0.2509 | 1.0623 | 1.0307 |
| No log | 3.3333 | 140 | 0.8701 | 0.2397 | 0.8701 | 0.9328 |
| No log | 3.3810 | 142 | 0.6972 | 0.3871 | 0.6972 | 0.8350 |
| No log | 3.4286 | 144 | 0.7350 | 0.3067 | 0.7350 | 0.8573 |
| No log | 3.4762 | 146 | 0.6852 | 0.3251 | 0.6852 | 0.8278 |
| No log | 3.5238 | 148 | 0.9988 | 0.2672 | 0.9988 | 0.9994 |
| No log | 3.5714 | 150 | 1.0571 | 0.2058 | 1.0571 | 1.0282 |
| No log | 3.6190 | 152 | 0.8332 | 0.2713 | 0.8332 | 0.9128 |
| No log | 3.6667 | 154 | 0.6074 | 0.3333 | 0.6074 | 0.7793 |
| No log | 3.7143 | 156 | 0.6357 | 0.3593 | 0.6357 | 0.7973 |
| No log | 3.7619 | 158 | 0.7875 | 0.3115 | 0.7875 | 0.8874 |
| No log | 3.8095 | 160 | 1.3698 | 0.2246 | 1.3698 | 1.1704 |
| No log | 3.8571 | 162 | 1.3890 | 0.2090 | 1.3890 | 1.1786 |
| No log | 3.9048 | 164 | 1.0298 | 0.3011 | 1.0298 | 1.0148 |
| No log | 3.9524 | 166 | 0.9681 | 0.3307 | 0.9681 | 0.9839 |
| No log | 4.0 | 168 | 0.8883 | 0.3333 | 0.8883 | 0.9425 |
| No log | 4.0476 | 170 | 0.8451 | 0.3735 | 0.8451 | 0.9193 |
| No log | 4.0952 | 172 | 1.0766 | 0.3143 | 1.0766 | 1.0376 |
| No log | 4.1429 | 174 | 1.2132 | 0.2254 | 1.2132 | 1.1014 |
| No log | 4.1905 | 176 | 1.4209 | 0.2000 | 1.4209 | 1.1920 |
| No log | 4.2381 | 178 | 1.2562 | 0.1850 | 1.2562 | 1.1208 |
| No log | 4.2857 | 180 | 0.7794 | 0.2922 | 0.7794 | 0.8828 |
| No log | 4.3333 | 182 | 0.7045 | 0.2759 | 0.7045 | 0.8393 |
| No log | 4.3810 | 184 | 0.7152 | 0.3518 | 0.7152 | 0.8457 |
| No log | 4.4286 | 186 | 0.8857 | 0.3071 | 0.8857 | 0.9411 |
| No log | 4.4762 | 188 | 1.3792 | 0.1951 | 1.3792 | 1.1744 |
| No log | 4.5238 | 190 | 1.6478 | 0.1549 | 1.6478 | 1.2836 |
| No log | 4.5714 | 192 | 1.4099 | 0.2192 | 1.4099 | 1.1874 |
| No log | 4.6190 | 194 | 0.8923 | 0.2812 | 0.8923 | 0.9446 |
| No log | 4.6667 | 196 | 0.7357 | 0.3195 | 0.7357 | 0.8578 |
| No log | 4.7143 | 198 | 0.7560 | 0.2340 | 0.7560 | 0.8695 |
| No log | 4.7619 | 200 | 0.7221 | 0.2838 | 0.7221 | 0.8498 |
| No log | 4.8095 | 202 | 0.8354 | 0.2340 | 0.8354 | 0.9140 |
| No log | 4.8571 | 204 | 1.1811 | 0.2111 | 1.1811 | 1.0868 |
| No log | 4.9048 | 206 | 1.1686 | 0.2111 | 1.1686 | 1.0810 |
| No log | 4.9524 | 208 | 0.8825 | 0.1680 | 0.8825 | 0.9394 |
| No log | 5.0 | 210 | 0.7059 | 0.3548 | 0.7059 | 0.8402 |
| No log | 5.0476 | 212 | 0.7341 | 0.2217 | 0.7341 | 0.8568 |
| No log | 5.0952 | 214 | 0.8546 | 0.3633 | 0.8546 | 0.9244 |
| No log | 5.1429 | 216 | 1.2335 | 0.1586 | 1.2335 | 1.1106 |
| No log | 5.1905 | 218 | 1.3401 | 0.1807 | 1.3401 | 1.1576 |
| No log | 5.2381 | 220 | 1.2896 | 0.1807 | 1.2896 | 1.1356 |
| No log | 5.2857 | 222 | 1.0244 | 0.2340 | 1.0244 | 1.0121 |
| No log | 5.3333 | 224 | 0.8723 | 0.3115 | 0.8723 | 0.9340 |
| No log | 5.3810 | 226 | 0.8636 | 0.3092 | 0.8636 | 0.9293 |
| No log | 5.4286 | 228 | 0.8981 | 0.2756 | 0.8981 | 0.9477 |
| No log | 5.4762 | 230 | 0.9439 | 0.1940 | 0.9439 | 0.9716 |
| No log | 5.5238 | 232 | 0.8449 | 0.2000 | 0.8449 | 0.9192 |
| No log | 5.5714 | 234 | 0.7627 | 0.2000 | 0.7627 | 0.8733 |
| No log | 5.6190 | 236 | 0.7754 | 0.2356 | 0.7754 | 0.8806 |
| No log | 5.6667 | 238 | 0.8590 | 0.1803 | 0.8590 | 0.9268 |
| No log | 5.7143 | 240 | 0.8268 | 0.1667 | 0.8269 | 0.9093 |
| No log | 5.7619 | 242 | 0.7868 | 0.1660 | 0.7868 | 0.8870 |
| No log | 5.8095 | 244 | 0.7894 | 0.1660 | 0.7894 | 0.8885 |
| No log | 5.8571 | 246 | 0.8241 | 0.1667 | 0.8241 | 0.9078 |
| No log | 5.9048 | 248 | 0.7099 | 0.3427 | 0.7099 | 0.8426 |
| No log | 5.9524 | 250 | 0.6426 | 0.3469 | 0.6426 | 0.8016 |
| No log | 6.0 | 252 | 0.6459 | 0.4175 | 0.6459 | 0.8037 |
| No log | 6.0476 | 254 | 0.6487 | 0.2653 | 0.6487 | 0.8054 |
| No log | 6.0952 | 256 | 0.7986 | 0.2000 | 0.7986 | 0.8936 |
| No log | 6.1429 | 258 | 1.0176 | 0.2000 | 1.0176 | 1.0088 |
| No log | 6.1905 | 260 | 0.9631 | 0.1942 | 0.9631 | 0.9814 |
| No log | 6.2381 | 262 | 0.8403 | 0.2569 | 0.8403 | 0.9167 |
| No log | 6.2857 | 264 | 0.8336 | 0.2569 | 0.8336 | 0.9130 |
| No log | 6.3333 | 266 | 0.9174 | 0.2234 | 0.9174 | 0.9578 |
| No log | 6.3810 | 268 | 0.8133 | 0.2510 | 0.8133 | 0.9018 |
| No log | 6.4286 | 270 | 0.6734 | 0.2919 | 0.6734 | 0.8206 |
| No log | 6.4762 | 272 | 0.6624 | 0.3786 | 0.6624 | 0.8139 |
| No log | 6.5238 | 274 | 0.6868 | 0.2227 | 0.6868 | 0.8288 |
| No log | 6.5714 | 276 | 0.8246 | 0.1795 | 0.8246 | 0.9081 |
| No log | 6.6190 | 278 | 0.8598 | 0.1475 | 0.8598 | 0.9273 |
| No log | 6.6667 | 280 | 0.7541 | 0.2150 | 0.7541 | 0.8684 |
| No log | 6.7143 | 282 | 0.6209 | 0.2370 | 0.6209 | 0.7880 |
| No log | 6.7619 | 284 | 0.5915 | 0.3609 | 0.5915 | 0.7691 |
| No log | 6.8095 | 286 | 0.5885 | 0.3609 | 0.5885 | 0.7671 |
| No log | 6.8571 | 288 | 0.5909 | 0.3374 | 0.5909 | 0.7687 |
| No log | 6.9048 | 290 | 0.6157 | 0.1902 | 0.6157 | 0.7846 |
| No log | 6.9524 | 292 | 0.6800 | 0.2323 | 0.6800 | 0.8246 |
| No log | 7.0 | 294 | 0.7365 | 0.2744 | 0.7365 | 0.8582 |
| No log | 7.0476 | 296 | 0.7469 | 0.2661 | 0.7469 | 0.8642 |
| No log | 7.0952 | 298 | 0.7098 | 0.2676 | 0.7098 | 0.8425 |
| No log | 7.1429 | 300 | 0.6775 | 0.4059 | 0.6775 | 0.8231 |
| No log | 7.1905 | 302 | 0.6917 | 0.3398 | 0.6917 | 0.8317 |
| No log | 7.2381 | 304 | 0.7198 | 0.2744 | 0.7198 | 0.8484 |
| No log | 7.2857 | 306 | 0.7683 | 0.2727 | 0.7683 | 0.8765 |
| No log | 7.3333 | 308 | 0.7307 | 0.2744 | 0.7307 | 0.8548 |
| No log | 7.3810 | 310 | 0.7231 | 0.2744 | 0.7231 | 0.8503 |
| No log | 7.4286 | 312 | 0.6900 | 0.2390 | 0.6900 | 0.8307 |
| No log | 7.4762 | 314 | 0.7241 | 0.2744 | 0.7241 | 0.8509 |
| No log | 7.5238 | 316 | 0.7384 | 0.2727 | 0.7384 | 0.8593 |
| No log | 7.5714 | 318 | 0.7406 | 0.2372 | 0.7406 | 0.8606 |
| No log | 7.6190 | 320 | 0.7724 | 0.2356 | 0.7724 | 0.8789 |
| No log | 7.6667 | 322 | 0.7970 | 0.2348 | 0.7970 | 0.8927 |
| No log | 7.7143 | 324 | 0.7656 | 0.2372 | 0.7656 | 0.8750 |
| No log | 7.7619 | 326 | 0.7910 | 0.2348 | 0.7910 | 0.8894 |
| No log | 7.8095 | 328 | 0.8318 | 0.2333 | 0.8318 | 0.9120 |
| No log | 7.8571 | 330 | 0.8111 | 0.2333 | 0.8111 | 0.9006 |
| No log | 7.9048 | 332 | 0.7149 | 0.2300 | 0.7149 | 0.8455 |
| No log | 7.9524 | 334 | 0.6665 | 0.3962 | 0.6665 | 0.8164 |
| No log | 8.0 | 336 | 0.6666 | 0.3962 | 0.6666 | 0.8164 |
| No log | 8.0476 | 338 | 0.6822 | 0.3962 | 0.6822 | 0.8259 |
| No log | 8.0952 | 340 | 0.7352 | 0.2308 | 0.7352 | 0.8574 |
| No log | 8.1429 | 342 | 0.8354 | 0.1730 | 0.8354 | 0.9140 |
| No log | 8.1905 | 344 | 0.9001 | 0.1746 | 0.9001 | 0.9487 |
| No log | 8.2381 | 346 | 0.8723 | 0.1746 | 0.8723 | 0.9340 |
| No log | 8.2857 | 348 | 0.8314 | 0.1730 | 0.8314 | 0.9118 |
| No log | 8.3333 | 350 | 0.7468 | 0.2077 | 0.7468 | 0.8642 |
| No log | 8.3810 | 352 | 0.6960 | 0.2709 | 0.6960 | 0.8343 |
| No log | 8.4286 | 354 | 0.6769 | 0.3010 | 0.6769 | 0.8227 |
| No log | 8.4762 | 356 | 0.6807 | 0.3010 | 0.6807 | 0.8251 |
| No log | 8.5238 | 358 | 0.7036 | 0.2308 | 0.7036 | 0.8388 |
| No log | 8.5714 | 360 | 0.7469 | 0.2381 | 0.7469 | 0.8642 |
| No log | 8.6190 | 362 | 0.7931 | 0.1718 | 0.7931 | 0.8906 |
| No log | 8.6667 | 364 | 0.8046 | 0.2068 | 0.8046 | 0.8970 |
| No log | 8.7143 | 366 | 0.7646 | 0.1698 | 0.7646 | 0.8744 |
| No log | 8.7619 | 368 | 0.7111 | 0.2381 | 0.7111 | 0.8433 |
| No log | 8.8095 | 370 | 0.6807 | 0.2709 | 0.6807 | 0.8250 |
| No log | 8.8571 | 372 | 0.6730 | 0.2709 | 0.6730 | 0.8204 |
| No log | 8.9048 | 374 | 0.6781 | 0.2709 | 0.6781 | 0.8234 |
| No log | 8.9524 | 376 | 0.6825 | 0.2390 | 0.6825 | 0.8262 |
| No log | 9.0 | 378 | 0.6885 | 0.2390 | 0.6885 | 0.8297 |
| No log | 9.0476 | 380 | 0.7175 | 0.2381 | 0.7175 | 0.8471 |
| No log | 9.0952 | 382 | 0.7584 | 0.2453 | 0.7584 | 0.8708 |
| No log | 9.1429 | 384 | 0.7842 | 0.2143 | 0.7842 | 0.8856 |
| No log | 9.1905 | 386 | 0.7735 | 0.2143 | 0.7735 | 0.8795 |
| No log | 9.2381 | 388 | 0.7643 | 0.2432 | 0.7643 | 0.8742 |
| No log | 9.2857 | 390 | 0.7556 | 0.2453 | 0.7556 | 0.8692 |
| No log | 9.3333 | 392 | 0.7312 | 0.2077 | 0.7312 | 0.8551 |
| No log | 9.3810 | 394 | 0.7121 | 0.2390 | 0.7121 | 0.8438 |
| No log | 9.4286 | 396 | 0.7033 | 0.2390 | 0.7033 | 0.8386 |
| No log | 9.4762 | 398 | 0.6959 | 0.2308 | 0.6959 | 0.8342 |
| No log | 9.5238 | 400 | 0.6969 | 0.2308 | 0.6969 | 0.8348 |
| No log | 9.5714 | 402 | 0.6917 | 0.2709 | 0.6917 | 0.8317 |
| No log | 9.6190 | 404 | 0.6794 | 0.3398 | 0.6794 | 0.8243 |
| No log | 9.6667 | 406 | 0.6732 | 0.3398 | 0.6732 | 0.8205 |
| No log | 9.7143 | 408 | 0.6736 | 0.3398 | 0.6736 | 0.8207 |
| No log | 9.7619 | 410 | 0.6767 | 0.3398 | 0.6767 | 0.8226 |
| No log | 9.8095 | 412 | 0.6816 | 0.2709 | 0.6816 | 0.8256 |
| No log | 9.8571 | 414 | 0.6887 | 0.2709 | 0.6887 | 0.8299 |
| No log | 9.9048 | 416 | 0.6921 | 0.2709 | 0.6921 | 0.8319 |
| No log | 9.9524 | 418 | 0.6937 | 0.2308 | 0.6937 | 0.8329 |
| No log | 10.0 | 420 | 0.6944 | 0.2308 | 0.6944 | 0.8333 |
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_k8_task3_organization
Base model
aubmindlab/bert-base-arabertv02