Instructions to use MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_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_run3_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_run3_AugV5_k10_task3_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k10_task3_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k10_task3_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_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: 0.7271
- Qwk: 0.2464
- Mse: 0.7271
- Rmse: 0.8527
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 | 1.0762 | -0.0154 | 1.0762 | 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 | 1.0736 | 0.0252 | 1.0736 | 1.0361 |
| No log | 1.4222 | 64 | 0.8701 | 0.0891 | 0.8701 | 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 | 1.2864 | 0.0270 | 1.2864 | 1.1342 |
| No log | 1.7333 | 78 | 0.9784 | 0.0717 | 0.9784 | 0.9891 |
| No log | 1.7778 | 80 | 0.7561 | 0.2577 | 0.7561 | 0.8695 |
| No log | 1.8222 | 82 | 0.8099 | 0.2153 | 0.8099 | 0.8999 |
| No log | 1.8667 | 84 | 1.4463 | 0.0464 | 1.4463 | 1.2026 |
| No log | 1.9111 | 86 | 1.4901 | 0.0502 | 1.4901 | 1.2207 |
| No log | 1.9556 | 88 | 1.2054 | 0.0262 | 1.2054 | 1.0979 |
| No log | 2.0 | 90 | 0.9639 | 0.0308 | 0.9639 | 0.9818 |
| No log | 2.0444 | 92 | 0.7750 | 0.2727 | 0.7750 | 0.8804 |
| No log | 2.0889 | 94 | 0.8084 | 0.2444 | 0.8084 | 0.8991 |
| No log | 2.1333 | 96 | 0.9615 | 0.0539 | 0.9615 | 0.9805 |
| No log | 2.1778 | 98 | 1.6188 | 0.1111 | 1.6188 | 1.2723 |
| No log | 2.2222 | 100 | 1.3504 | 0.1169 | 1.3504 | 1.1621 |
| No log | 2.2667 | 102 | 0.8184 | 0.1538 | 0.8184 | 0.9047 |
| No log | 2.3111 | 104 | 0.8760 | 0.2146 | 0.8760 | 0.9359 |
| No log | 2.3556 | 106 | 0.9249 | 0.2489 | 0.9249 | 0.9617 |
| No log | 2.4 | 108 | 0.9554 | 0.2208 | 0.9554 | 0.9774 |
| No log | 2.4444 | 110 | 1.3338 | 0.0789 | 1.3338 | 1.1549 |
| No log | 2.4889 | 112 | 0.8857 | 0.1269 | 0.8857 | 0.9411 |
| No log | 2.5333 | 114 | 0.7704 | 0.1919 | 0.7704 | 0.8777 |
| No log | 2.5778 | 116 | 0.8005 | 0.2315 | 0.8005 | 0.8947 |
| No log | 2.6222 | 118 | 0.7511 | 0.2350 | 0.7511 | 0.8666 |
| No log | 2.6667 | 120 | 0.8242 | 0.1600 | 0.8242 | 0.9079 |
| No log | 2.7111 | 122 | 1.1665 | 0.0312 | 1.1665 | 1.0800 |
| No log | 2.7556 | 124 | 1.1751 | 0.0111 | 1.1751 | 1.0840 |
| No log | 2.8 | 126 | 0.7279 | 0.2513 | 0.7279 | 0.8532 |
| No log | 2.8444 | 128 | 0.7175 | 0.2626 | 0.7175 | 0.8471 |
| No log | 2.8889 | 130 | 0.7620 | 0.2000 | 0.7620 | 0.8729 |
| No log | 2.9333 | 132 | 0.8253 | 0.1269 | 0.8253 | 0.9085 |
| No log | 2.9778 | 134 | 1.0385 | -0.0164 | 1.0385 | 1.0191 |
| No log | 3.0222 | 136 | 1.0809 | -0.0164 | 1.0809 | 1.0396 |
| No log | 3.0667 | 138 | 0.7979 | 0.1086 | 0.7979 | 0.8933 |
| No log | 3.1111 | 140 | 0.8275 | 0.0459 | 0.8275 | 0.9097 |
| No log | 3.1556 | 142 | 0.7615 | 0.2889 | 0.7615 | 0.8727 |
| No log | 3.2 | 144 | 1.1626 | 0.0840 | 1.1626 | 1.0783 |
| No log | 3.2444 | 146 | 1.8161 | 0.0787 | 1.8161 | 1.3476 |
| No log | 3.2889 | 148 | 1.3988 | 0.1345 | 1.3988 | 1.1827 |
| No log | 3.3333 | 150 | 0.6676 | 0.1910 | 0.6676 | 0.8171 |
| No log | 3.3778 | 152 | 0.6594 | 0.2393 | 0.6594 | 0.8120 |
| No log | 3.4222 | 154 | 0.6507 | 0.2749 | 0.6507 | 0.8066 |
| No log | 3.4667 | 156 | 0.6680 | 0.2258 | 0.6680 | 0.8173 |
| No log | 3.5111 | 158 | 0.7360 | 0.1568 | 0.7360 | 0.8579 |
| No log | 3.5556 | 160 | 0.7324 | 0.2653 | 0.7324 | 0.8558 |
| No log | 3.6 | 162 | 0.7171 | 0.2990 | 0.7171 | 0.8468 |
| No log | 3.6444 | 164 | 0.7418 | 0.2442 | 0.7418 | 0.8613 |
| No log | 3.6889 | 166 | 0.7472 | 0.2965 | 0.7472 | 0.8644 |
| No log | 3.7333 | 168 | 0.9124 | 0.1776 | 0.9124 | 0.9552 |
| No log | 3.7778 | 170 | 0.9227 | 0.1786 | 0.9227 | 0.9606 |
| No log | 3.8222 | 172 | 0.7126 | 0.2245 | 0.7126 | 0.8441 |
| No log | 3.8667 | 174 | 0.8054 | 0.2676 | 0.8054 | 0.8974 |
| No log | 3.9111 | 176 | 0.8899 | 0.1273 | 0.8899 | 0.9433 |
| No log | 3.9556 | 178 | 0.6876 | 0.2787 | 0.6876 | 0.8292 |
| No log | 4.0 | 180 | 0.8965 | 0.1453 | 0.8965 | 0.9469 |
| No log | 4.0444 | 182 | 1.2696 | 0.1409 | 1.2696 | 1.1268 |
| No log | 4.0889 | 184 | 1.0276 | 0.1027 | 1.0276 | 1.0137 |
| No log | 4.1333 | 186 | 0.6673 | 0.1411 | 0.6673 | 0.8169 |
| No log | 4.1778 | 188 | 0.7583 | 0.1357 | 0.7583 | 0.8708 |
| No log | 4.2222 | 190 | 0.7611 | 0.1841 | 0.7611 | 0.8724 |
| No log | 4.2667 | 192 | 0.6702 | 0.3023 | 0.6702 | 0.8187 |
| No log | 4.3111 | 194 | 0.8270 | 0.0714 | 0.8270 | 0.9094 |
| No log | 4.3556 | 196 | 1.0507 | 0.1292 | 1.0507 | 1.0250 |
| No log | 4.4 | 198 | 0.9032 | 0.1392 | 0.9032 | 0.9504 |
| No log | 4.4444 | 200 | 0.8283 | 0.1712 | 0.8283 | 0.9101 |
| No log | 4.4889 | 202 | 0.7188 | 0.2653 | 0.7188 | 0.8478 |
| No log | 4.5333 | 204 | 0.7356 | 0.2653 | 0.7356 | 0.8577 |
| No log | 4.5778 | 206 | 0.8409 | 0.0909 | 0.8409 | 0.9170 |
| No log | 4.6222 | 208 | 0.8219 | 0.1238 | 0.8219 | 0.9066 |
| No log | 4.6667 | 210 | 0.6988 | 0.2432 | 0.6988 | 0.8360 |
| No log | 4.7111 | 212 | 0.6802 | 0.3161 | 0.6802 | 0.8248 |
| No log | 4.7556 | 214 | 0.6128 | 0.3520 | 0.6128 | 0.7828 |
| No log | 4.8 | 216 | 0.6942 | 0.2165 | 0.6942 | 0.8332 |
| No log | 4.8444 | 218 | 0.6520 | 0.25 | 0.6520 | 0.8074 |
| No log | 4.8889 | 220 | 0.6064 | 0.2865 | 0.6064 | 0.7787 |
| No log | 4.9333 | 222 | 0.5492 | 0.3797 | 0.5492 | 0.7411 |
| No log | 4.9778 | 224 | 0.5589 | 0.3913 | 0.5589 | 0.7476 |
| No log | 5.0222 | 226 | 0.5724 | 0.4105 | 0.5724 | 0.7565 |
| No log | 5.0667 | 228 | 0.6337 | 0.3061 | 0.6337 | 0.7961 |
| No log | 5.1111 | 230 | 0.6528 | 0.3433 | 0.6528 | 0.8080 |
| No log | 5.1556 | 232 | 0.6671 | 0.3684 | 0.6671 | 0.8168 |
| No log | 5.2 | 234 | 0.9119 | 0.1756 | 0.9119 | 0.9549 |
| No log | 5.2444 | 236 | 1.0690 | 0.1515 | 1.0690 | 1.0339 |
| No log | 5.2889 | 238 | 0.8865 | 0.1673 | 0.8865 | 0.9416 |
| No log | 5.3333 | 240 | 0.6931 | 0.3561 | 0.6931 | 0.8325 |
| No log | 5.3778 | 242 | 0.7651 | 0.2432 | 0.7651 | 0.8747 |
| No log | 5.4222 | 244 | 0.7098 | 0.3010 | 0.7098 | 0.8425 |
| No log | 5.4667 | 246 | 0.6972 | 0.2653 | 0.6972 | 0.8350 |
| No log | 5.5111 | 248 | 0.7088 | 0.1919 | 0.7088 | 0.8419 |
| No log | 5.5556 | 250 | 0.6954 | 0.2941 | 0.6954 | 0.8339 |
| No log | 5.6 | 252 | 0.7927 | 0.2146 | 0.7927 | 0.8904 |
| No log | 5.6444 | 254 | 0.8846 | 0.2333 | 0.8846 | 0.9405 |
| No log | 5.6889 | 256 | 0.7679 | 0.2068 | 0.7679 | 0.8763 |
| No log | 5.7333 | 258 | 0.7817 | 0.2222 | 0.7817 | 0.8841 |
| No log | 5.7778 | 260 | 0.9592 | 0.1453 | 0.9592 | 0.9794 |
| No log | 5.8222 | 262 | 0.8759 | 0.2143 | 0.8759 | 0.9359 |
| No log | 5.8667 | 264 | 0.7547 | 0.2308 | 0.7547 | 0.8687 |
| No log | 5.9111 | 266 | 0.6917 | 0.2917 | 0.6917 | 0.8317 |
| No log | 5.9556 | 268 | 0.6913 | 0.2577 | 0.6913 | 0.8315 |
| No log | 6.0 | 270 | 0.7005 | 0.2315 | 0.7005 | 0.8369 |
| No log | 6.0444 | 272 | 0.7117 | 0.1753 | 0.7117 | 0.8436 |
| No log | 6.0889 | 274 | 0.6497 | 0.2670 | 0.6497 | 0.8061 |
| No log | 6.1333 | 276 | 0.6116 | 0.2179 | 0.6116 | 0.7820 |
| No log | 6.1778 | 278 | 0.6399 | 0.2670 | 0.6399 | 0.7999 |
| No log | 6.2222 | 280 | 0.6998 | 0.25 | 0.6998 | 0.8365 |
| No log | 6.2667 | 282 | 0.6563 | 0.2670 | 0.6563 | 0.8101 |
| No log | 6.3111 | 284 | 0.6364 | 0.2941 | 0.6364 | 0.7978 |
| No log | 6.3556 | 286 | 0.6643 | 0.2941 | 0.6643 | 0.8151 |
| No log | 6.4 | 288 | 0.7627 | 0.1781 | 0.7627 | 0.8733 |
| No log | 6.4444 | 290 | 0.8310 | 0.1855 | 0.8310 | 0.9116 |
| No log | 6.4889 | 292 | 0.8521 | 0.1927 | 0.8521 | 0.9231 |
| No log | 6.5333 | 294 | 0.7856 | 0.2442 | 0.7856 | 0.8864 |
| No log | 6.5778 | 296 | 0.7451 | 0.2917 | 0.7451 | 0.8632 |
| No log | 6.6222 | 298 | 0.7517 | 0.2871 | 0.7517 | 0.8670 |
| No log | 6.6667 | 300 | 0.8125 | 0.1238 | 0.8125 | 0.9014 |
| No log | 6.7111 | 302 | 0.7527 | 0.1238 | 0.7527 | 0.8676 |
| No log | 6.7556 | 304 | 0.6793 | 0.2258 | 0.6793 | 0.8242 |
| No log | 6.8 | 306 | 0.6623 | 0.3191 | 0.6623 | 0.8138 |
| No log | 6.8444 | 308 | 0.6702 | 0.3191 | 0.6702 | 0.8187 |
| No log | 6.8889 | 310 | 0.6892 | 0.2917 | 0.6892 | 0.8302 |
| No log | 6.9333 | 312 | 0.7084 | 0.2917 | 0.7084 | 0.8417 |
| No log | 6.9778 | 314 | 0.7189 | 0.2536 | 0.7189 | 0.8479 |
| No log | 7.0222 | 316 | 0.7330 | 0.2536 | 0.7330 | 0.8561 |
| No log | 7.0667 | 318 | 0.7276 | 0.2917 | 0.7276 | 0.8530 |
| No log | 7.1111 | 320 | 0.7215 | 0.2917 | 0.7215 | 0.8494 |
| No log | 7.1556 | 322 | 0.7062 | 0.2917 | 0.7062 | 0.8403 |
| No log | 7.2 | 324 | 0.6794 | 0.2727 | 0.6794 | 0.8243 |
| No log | 7.2444 | 326 | 0.6628 | 0.3161 | 0.6628 | 0.8141 |
| No log | 7.2889 | 328 | 0.6557 | 0.2941 | 0.6557 | 0.8097 |
| No log | 7.3333 | 330 | 0.6525 | 0.2265 | 0.6525 | 0.8078 |
| No log | 7.3778 | 332 | 0.6813 | 0.1556 | 0.6813 | 0.8254 |
| No log | 7.4222 | 334 | 0.7107 | 0.1556 | 0.7107 | 0.8430 |
| No log | 7.4667 | 336 | 0.6888 | 0.2258 | 0.6888 | 0.8299 |
| No log | 7.5111 | 338 | 0.6775 | 0.2727 | 0.6775 | 0.8231 |
| No log | 7.5556 | 340 | 0.7094 | 0.2549 | 0.7094 | 0.8422 |
| No log | 7.6 | 342 | 0.7099 | 0.2549 | 0.7099 | 0.8426 |
| No log | 7.6444 | 344 | 0.6920 | 0.3469 | 0.6920 | 0.8319 |
| No log | 7.6889 | 346 | 0.7077 | 0.2692 | 0.7077 | 0.8413 |
| No log | 7.7333 | 348 | 0.7609 | 0.2593 | 0.7609 | 0.8723 |
| No log | 7.7778 | 350 | 0.7693 | 0.2593 | 0.7693 | 0.8771 |
| No log | 7.8222 | 352 | 0.7346 | 0.2165 | 0.7346 | 0.8571 |
| No log | 7.8667 | 354 | 0.7092 | 0.2165 | 0.7092 | 0.8421 |
| No log | 7.9111 | 356 | 0.7082 | 0.2165 | 0.7082 | 0.8415 |
| No log | 7.9556 | 358 | 0.7406 | 0.2986 | 0.7406 | 0.8606 |
| No log | 8.0 | 360 | 0.7697 | 0.1928 | 0.7697 | 0.8773 |
| No log | 8.0444 | 362 | 0.7529 | 0.2294 | 0.7529 | 0.8677 |
| No log | 8.0889 | 364 | 0.7204 | 0.2709 | 0.7204 | 0.8488 |
| No log | 8.1333 | 366 | 0.6796 | 0.2593 | 0.6796 | 0.8244 |
| No log | 8.1778 | 368 | 0.6777 | 0.3171 | 0.6777 | 0.8233 |
| No log | 8.2222 | 370 | 0.7068 | 0.3498 | 0.7068 | 0.8407 |
| No log | 8.2667 | 372 | 0.7092 | 0.2762 | 0.7092 | 0.8422 |
| No log | 8.3111 | 374 | 0.7129 | 0.2692 | 0.7129 | 0.8443 |
| No log | 8.3556 | 376 | 0.7594 | 0.1855 | 0.7594 | 0.8715 |
| No log | 8.4 | 378 | 0.7809 | 0.2212 | 0.7809 | 0.8837 |
| No log | 8.4444 | 380 | 0.7525 | 0.1855 | 0.7525 | 0.8675 |
| No log | 8.4889 | 382 | 0.7375 | 0.2637 | 0.7375 | 0.8588 |
| No log | 8.5333 | 384 | 0.7134 | 0.2464 | 0.7134 | 0.8446 |
| No log | 8.5778 | 386 | 0.7030 | 0.2549 | 0.7030 | 0.8385 |
| No log | 8.6222 | 388 | 0.6981 | 0.2762 | 0.6981 | 0.8355 |
| No log | 8.6667 | 390 | 0.6956 | 0.2821 | 0.6956 | 0.8340 |
| No log | 8.7111 | 392 | 0.7130 | 0.2653 | 0.7130 | 0.8444 |
| No log | 8.7556 | 394 | 0.7340 | 0.2637 | 0.7340 | 0.8567 |
| No log | 8.8 | 396 | 0.7224 | 0.2637 | 0.7224 | 0.8499 |
| No log | 8.8444 | 398 | 0.7143 | 0.2637 | 0.7143 | 0.8451 |
| No log | 8.8889 | 400 | 0.6927 | 0.2670 | 0.6927 | 0.8323 |
| No log | 8.9333 | 402 | 0.6840 | 0.2081 | 0.6840 | 0.8270 |
| No log | 8.9778 | 404 | 0.6870 | 0.2081 | 0.6870 | 0.8289 |
| No log | 9.0222 | 406 | 0.6872 | 0.2709 | 0.6872 | 0.8290 |
| No log | 9.0667 | 408 | 0.6931 | 0.2727 | 0.6931 | 0.8325 |
| No log | 9.1111 | 410 | 0.6994 | 0.28 | 0.6994 | 0.8363 |
| No log | 9.1556 | 412 | 0.7122 | 0.2475 | 0.7122 | 0.8439 |
| No log | 9.2 | 414 | 0.7208 | 0.2464 | 0.7208 | 0.8490 |
| No log | 9.2444 | 416 | 0.7320 | 0.2637 | 0.7320 | 0.8556 |
| No log | 9.2889 | 418 | 0.7426 | 0.2986 | 0.7426 | 0.8618 |
| No log | 9.3333 | 420 | 0.7568 | 0.2593 | 0.7568 | 0.8699 |
| No log | 9.3778 | 422 | 0.7503 | 0.2593 | 0.7503 | 0.8662 |
| No log | 9.4222 | 424 | 0.7452 | 0.2986 | 0.7452 | 0.8632 |
| No log | 9.4667 | 426 | 0.7371 | 0.3010 | 0.7371 | 0.8585 |
| No log | 9.5111 | 428 | 0.7352 | 0.2637 | 0.7352 | 0.8574 |
| No log | 9.5556 | 430 | 0.7263 | 0.2464 | 0.7263 | 0.8522 |
| No log | 9.6 | 432 | 0.7211 | 0.2475 | 0.7211 | 0.8492 |
| No log | 9.6444 | 434 | 0.7223 | 0.2475 | 0.7223 | 0.8499 |
| No log | 9.6889 | 436 | 0.7235 | 0.2475 | 0.7235 | 0.8506 |
| No log | 9.7333 | 438 | 0.7236 | 0.2475 | 0.7236 | 0.8507 |
| No log | 9.7778 | 440 | 0.7228 | 0.2475 | 0.7228 | 0.8502 |
| No log | 9.8222 | 442 | 0.7237 | 0.2475 | 0.7237 | 0.8507 |
| No log | 9.8667 | 444 | 0.7248 | 0.2475 | 0.7248 | 0.8513 |
| No log | 9.9111 | 446 | 0.7260 | 0.2464 | 0.7260 | 0.8521 |
| No log | 9.9556 | 448 | 0.7270 | 0.2464 | 0.7270 | 0.8526 |
| No log | 10.0 | 450 | 0.7271 | 0.2464 | 0.7271 | 0.8527 |
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_run3_AugV5_k10_task3_organization
Base model
aubmindlab/bert-base-arabertv02