Instructions to use MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task5_organization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task5_organization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task5_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task5_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task5_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_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: 0.5891
- Qwk: 0.6742
- Mse: 0.5891
- Rmse: 0.7675
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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 0.2857 | 2 | 4.1544 | 0.0024 | 4.1544 | 2.0382 |
| No log | 0.5714 | 4 | 2.2714 | 0.0775 | 2.2714 | 1.5071 |
| No log | 0.8571 | 6 | 1.3687 | -0.0256 | 1.3687 | 1.1699 |
| No log | 1.1429 | 8 | 1.0951 | 0.1944 | 1.0951 | 1.0465 |
| No log | 1.4286 | 10 | 1.0545 | 0.1981 | 1.0545 | 1.0269 |
| No log | 1.7143 | 12 | 1.1177 | 0.1474 | 1.1177 | 1.0572 |
| No log | 2.0 | 14 | 1.2045 | 0.1971 | 1.2045 | 1.0975 |
| No log | 2.2857 | 16 | 1.2755 | 0.1171 | 1.2755 | 1.1294 |
| No log | 2.5714 | 18 | 1.0260 | 0.3310 | 1.0260 | 1.0129 |
| No log | 2.8571 | 20 | 1.0369 | 0.2773 | 1.0369 | 1.0183 |
| No log | 3.1429 | 22 | 1.0260 | 0.2390 | 1.0260 | 1.0129 |
| No log | 3.4286 | 24 | 0.9386 | 0.2541 | 0.9386 | 0.9688 |
| No log | 3.7143 | 26 | 1.0257 | 0.2969 | 1.0257 | 1.0128 |
| No log | 4.0 | 28 | 1.0761 | 0.2731 | 1.0761 | 1.0374 |
| No log | 4.2857 | 30 | 1.0658 | 0.2354 | 1.0658 | 1.0324 |
| No log | 4.5714 | 32 | 0.8588 | 0.3508 | 0.8588 | 0.9267 |
| No log | 4.8571 | 34 | 0.8164 | 0.4234 | 0.8164 | 0.9035 |
| No log | 5.1429 | 36 | 0.8350 | 0.4220 | 0.8350 | 0.9138 |
| No log | 5.4286 | 38 | 0.8403 | 0.4480 | 0.8403 | 0.9167 |
| No log | 5.7143 | 40 | 0.7818 | 0.4413 | 0.7818 | 0.8842 |
| No log | 6.0 | 42 | 0.8323 | 0.6014 | 0.8323 | 0.9123 |
| No log | 6.2857 | 44 | 1.1685 | 0.3021 | 1.1685 | 1.0810 |
| No log | 6.5714 | 46 | 1.0084 | 0.4589 | 1.0084 | 1.0042 |
| No log | 6.8571 | 48 | 0.9482 | 0.5070 | 0.9482 | 0.9738 |
| No log | 7.1429 | 50 | 1.1109 | 0.4001 | 1.1109 | 1.0540 |
| No log | 7.4286 | 52 | 0.9807 | 0.5066 | 0.9807 | 0.9903 |
| No log | 7.7143 | 54 | 0.7219 | 0.5697 | 0.7219 | 0.8497 |
| No log | 8.0 | 56 | 0.7905 | 0.5870 | 0.7905 | 0.8891 |
| No log | 8.2857 | 58 | 0.9697 | 0.4585 | 0.9697 | 0.9847 |
| No log | 8.5714 | 60 | 0.8305 | 0.5870 | 0.8305 | 0.9113 |
| No log | 8.8571 | 62 | 0.6908 | 0.6494 | 0.6908 | 0.8312 |
| No log | 9.1429 | 64 | 0.8961 | 0.5239 | 0.8961 | 0.9466 |
| No log | 9.4286 | 66 | 1.1638 | 0.4421 | 1.1638 | 1.0788 |
| No log | 9.7143 | 68 | 1.0376 | 0.4642 | 1.0376 | 1.0186 |
| No log | 10.0 | 70 | 0.7428 | 0.6565 | 0.7428 | 0.8619 |
| No log | 10.2857 | 72 | 0.6680 | 0.6241 | 0.6680 | 0.8173 |
| No log | 10.5714 | 74 | 0.7634 | 0.5845 | 0.7634 | 0.8737 |
| No log | 10.8571 | 76 | 0.7480 | 0.6233 | 0.7480 | 0.8649 |
| No log | 11.1429 | 78 | 0.6594 | 0.6187 | 0.6594 | 0.8121 |
| No log | 11.4286 | 80 | 0.7400 | 0.6599 | 0.7400 | 0.8602 |
| No log | 11.7143 | 82 | 0.7482 | 0.6308 | 0.7482 | 0.8650 |
| No log | 12.0 | 84 | 0.6937 | 0.6615 | 0.6937 | 0.8329 |
| No log | 12.2857 | 86 | 0.6661 | 0.6085 | 0.6661 | 0.8162 |
| No log | 12.5714 | 88 | 0.6776 | 0.5410 | 0.6776 | 0.8231 |
| No log | 12.8571 | 90 | 0.6557 | 0.6284 | 0.6557 | 0.8097 |
| No log | 13.1429 | 92 | 0.7020 | 0.6344 | 0.7020 | 0.8378 |
| No log | 13.4286 | 94 | 0.8018 | 0.5037 | 0.8018 | 0.8954 |
| No log | 13.7143 | 96 | 0.7699 | 0.5629 | 0.7699 | 0.8775 |
| No log | 14.0 | 98 | 0.8433 | 0.6069 | 0.8433 | 0.9183 |
| No log | 14.2857 | 100 | 0.9941 | 0.5005 | 0.9941 | 0.9971 |
| No log | 14.5714 | 102 | 0.9751 | 0.5005 | 0.9751 | 0.9875 |
| No log | 14.8571 | 104 | 0.7779 | 0.6357 | 0.7779 | 0.8820 |
| No log | 15.1429 | 106 | 0.7070 | 0.6618 | 0.7070 | 0.8408 |
| No log | 15.4286 | 108 | 0.6833 | 0.5995 | 0.6833 | 0.8266 |
| No log | 15.7143 | 110 | 0.6944 | 0.5972 | 0.6944 | 0.8333 |
| No log | 16.0 | 112 | 0.7646 | 0.6394 | 0.7646 | 0.8744 |
| No log | 16.2857 | 114 | 0.8519 | 0.5370 | 0.8519 | 0.9230 |
| No log | 16.5714 | 116 | 0.7881 | 0.5151 | 0.7881 | 0.8877 |
| No log | 16.8571 | 118 | 0.6779 | 0.6306 | 0.6779 | 0.8234 |
| No log | 17.1429 | 120 | 0.6711 | 0.6167 | 0.6711 | 0.8192 |
| No log | 17.4286 | 122 | 0.6696 | 0.6275 | 0.6696 | 0.8183 |
| No log | 17.7143 | 124 | 0.7505 | 0.6633 | 0.7505 | 0.8663 |
| No log | 18.0 | 126 | 0.8089 | 0.5981 | 0.8089 | 0.8994 |
| No log | 18.2857 | 128 | 0.7447 | 0.6661 | 0.7447 | 0.8630 |
| No log | 18.5714 | 130 | 0.6743 | 0.6526 | 0.6743 | 0.8212 |
| No log | 18.8571 | 132 | 0.6713 | 0.6148 | 0.6713 | 0.8193 |
| No log | 19.1429 | 134 | 0.6670 | 0.5975 | 0.6670 | 0.8167 |
| No log | 19.4286 | 136 | 0.6474 | 0.6046 | 0.6474 | 0.8046 |
| No log | 19.7143 | 138 | 0.6834 | 0.6039 | 0.6834 | 0.8267 |
| No log | 20.0 | 140 | 0.7341 | 0.6032 | 0.7341 | 0.8568 |
| No log | 20.2857 | 142 | 0.7316 | 0.6226 | 0.7316 | 0.8553 |
| No log | 20.5714 | 144 | 0.6975 | 0.6820 | 0.6975 | 0.8352 |
| No log | 20.8571 | 146 | 0.7315 | 0.6457 | 0.7315 | 0.8553 |
| No log | 21.1429 | 148 | 0.7727 | 0.6029 | 0.7727 | 0.8790 |
| No log | 21.4286 | 150 | 0.8022 | 0.5148 | 0.8022 | 0.8957 |
| No log | 21.7143 | 152 | 0.7767 | 0.5583 | 0.7767 | 0.8813 |
| No log | 22.0 | 154 | 0.7297 | 0.6811 | 0.7297 | 0.8542 |
| No log | 22.2857 | 156 | 0.6805 | 0.6820 | 0.6805 | 0.8249 |
| No log | 22.5714 | 158 | 0.6386 | 0.6772 | 0.6386 | 0.7991 |
| No log | 22.8571 | 160 | 0.6347 | 0.6465 | 0.6347 | 0.7967 |
| No log | 23.1429 | 162 | 0.6359 | 0.7018 | 0.6359 | 0.7974 |
| No log | 23.4286 | 164 | 0.6719 | 0.6692 | 0.6719 | 0.8197 |
| No log | 23.7143 | 166 | 0.7611 | 0.6226 | 0.7611 | 0.8724 |
| No log | 24.0 | 168 | 0.8091 | 0.5258 | 0.8091 | 0.8995 |
| No log | 24.2857 | 170 | 0.7352 | 0.6226 | 0.7352 | 0.8574 |
| No log | 24.5714 | 172 | 0.6517 | 0.6803 | 0.6517 | 0.8073 |
| No log | 24.8571 | 174 | 0.6352 | 0.7078 | 0.6352 | 0.7970 |
| No log | 25.1429 | 176 | 0.6477 | 0.6835 | 0.6477 | 0.8048 |
| No log | 25.4286 | 178 | 0.6707 | 0.6906 | 0.6707 | 0.8190 |
| No log | 25.7143 | 180 | 0.7303 | 0.5898 | 0.7303 | 0.8546 |
| No log | 26.0 | 182 | 0.7670 | 0.6014 | 0.7670 | 0.8758 |
| No log | 26.2857 | 184 | 0.7283 | 0.6226 | 0.7283 | 0.8534 |
| No log | 26.5714 | 186 | 0.6593 | 0.6906 | 0.6593 | 0.8120 |
| No log | 26.8571 | 188 | 0.6307 | 0.6456 | 0.6307 | 0.7942 |
| No log | 27.1429 | 190 | 0.6438 | 0.6931 | 0.6438 | 0.8024 |
| No log | 27.4286 | 192 | 0.6659 | 0.7025 | 0.6659 | 0.8160 |
| No log | 27.7143 | 194 | 0.7590 | 0.6045 | 0.7590 | 0.8712 |
| No log | 28.0 | 196 | 0.8346 | 0.4866 | 0.8346 | 0.9136 |
| No log | 28.2857 | 198 | 0.7868 | 0.5565 | 0.7868 | 0.8870 |
| No log | 28.5714 | 200 | 0.6699 | 0.7071 | 0.6699 | 0.8185 |
| No log | 28.8571 | 202 | 0.6352 | 0.6963 | 0.6352 | 0.7970 |
| No log | 29.1429 | 204 | 0.6284 | 0.6963 | 0.6284 | 0.7927 |
| No log | 29.4286 | 206 | 0.6085 | 0.6963 | 0.6085 | 0.7801 |
| No log | 29.7143 | 208 | 0.6348 | 0.6906 | 0.6348 | 0.7967 |
| No log | 30.0 | 210 | 0.7044 | 0.6353 | 0.7044 | 0.8393 |
| No log | 30.2857 | 212 | 0.7541 | 0.6266 | 0.7541 | 0.8684 |
| No log | 30.5714 | 214 | 0.7153 | 0.6307 | 0.7153 | 0.8458 |
| No log | 30.8571 | 216 | 0.6501 | 0.6705 | 0.6501 | 0.8063 |
| No log | 31.1429 | 218 | 0.6334 | 0.6319 | 0.6334 | 0.7958 |
| No log | 31.4286 | 220 | 0.6355 | 0.6138 | 0.6355 | 0.7972 |
| No log | 31.7143 | 222 | 0.6262 | 0.6659 | 0.6262 | 0.7913 |
| No log | 32.0 | 224 | 0.6322 | 0.6745 | 0.6322 | 0.7951 |
| No log | 32.2857 | 226 | 0.6574 | 0.6745 | 0.6574 | 0.8108 |
| No log | 32.5714 | 228 | 0.6613 | 0.6745 | 0.6613 | 0.8132 |
| No log | 32.8571 | 230 | 0.6638 | 0.6561 | 0.6638 | 0.8147 |
| No log | 33.1429 | 232 | 0.6703 | 0.6298 | 0.6703 | 0.8187 |
| No log | 33.4286 | 234 | 0.6466 | 0.6120 | 0.6466 | 0.8041 |
| No log | 33.7143 | 236 | 0.6286 | 0.6561 | 0.6286 | 0.7929 |
| No log | 34.0 | 238 | 0.6609 | 0.6812 | 0.6609 | 0.8130 |
| No log | 34.2857 | 240 | 0.6852 | 0.6590 | 0.6852 | 0.8278 |
| No log | 34.5714 | 242 | 0.6457 | 0.6497 | 0.6457 | 0.8035 |
| No log | 34.8571 | 244 | 0.6089 | 0.6282 | 0.6089 | 0.7803 |
| No log | 35.1429 | 246 | 0.6082 | 0.6076 | 0.6082 | 0.7799 |
| No log | 35.4286 | 248 | 0.6146 | 0.5871 | 0.6146 | 0.7839 |
| No log | 35.7143 | 250 | 0.6284 | 0.5833 | 0.6284 | 0.7927 |
| No log | 36.0 | 252 | 0.6477 | 0.6021 | 0.6477 | 0.8048 |
| No log | 36.2857 | 254 | 0.6622 | 0.6661 | 0.6622 | 0.8138 |
| No log | 36.5714 | 256 | 0.6700 | 0.6661 | 0.6700 | 0.8185 |
| No log | 36.8571 | 258 | 0.6952 | 0.6661 | 0.6952 | 0.8338 |
| No log | 37.1429 | 260 | 0.7095 | 0.6661 | 0.7095 | 0.8423 |
| No log | 37.4286 | 262 | 0.7102 | 0.6386 | 0.7102 | 0.8428 |
| No log | 37.7143 | 264 | 0.6602 | 0.6970 | 0.6602 | 0.8125 |
| No log | 38.0 | 266 | 0.6192 | 0.6795 | 0.6192 | 0.7869 |
| No log | 38.2857 | 268 | 0.6236 | 0.6725 | 0.6236 | 0.7897 |
| No log | 38.5714 | 270 | 0.6203 | 0.6536 | 0.6203 | 0.7876 |
| No log | 38.8571 | 272 | 0.5995 | 0.6708 | 0.5995 | 0.7743 |
| No log | 39.1429 | 274 | 0.6010 | 0.6708 | 0.6010 | 0.7753 |
| No log | 39.4286 | 276 | 0.6467 | 0.6611 | 0.6467 | 0.8042 |
| No log | 39.7143 | 278 | 0.6820 | 0.6411 | 0.6820 | 0.8258 |
| No log | 40.0 | 280 | 0.7178 | 0.6308 | 0.7178 | 0.8472 |
| No log | 40.2857 | 282 | 0.7538 | 0.6317 | 0.7538 | 0.8682 |
| No log | 40.5714 | 284 | 0.7610 | 0.5909 | 0.7610 | 0.8724 |
| No log | 40.8571 | 286 | 0.6940 | 0.6308 | 0.6940 | 0.8331 |
| No log | 41.1429 | 288 | 0.6226 | 0.6526 | 0.6226 | 0.7890 |
| No log | 41.4286 | 290 | 0.6145 | 0.6556 | 0.6145 | 0.7839 |
| No log | 41.7143 | 292 | 0.6049 | 0.6742 | 0.6049 | 0.7778 |
| No log | 42.0 | 294 | 0.6020 | 0.6282 | 0.6020 | 0.7759 |
| No log | 42.2857 | 296 | 0.6039 | 0.6282 | 0.6039 | 0.7771 |
| No log | 42.5714 | 298 | 0.6095 | 0.6742 | 0.6095 | 0.7807 |
| No log | 42.8571 | 300 | 0.6178 | 0.6602 | 0.6178 | 0.7860 |
| No log | 43.1429 | 302 | 0.6129 | 0.6488 | 0.6129 | 0.7829 |
| No log | 43.4286 | 304 | 0.6078 | 0.6555 | 0.6078 | 0.7796 |
| No log | 43.7143 | 306 | 0.6027 | 0.6584 | 0.6027 | 0.7763 |
| No log | 44.0 | 308 | 0.5985 | 0.6584 | 0.5985 | 0.7736 |
| No log | 44.2857 | 310 | 0.5956 | 0.6625 | 0.5956 | 0.7717 |
| No log | 44.5714 | 312 | 0.5919 | 0.6625 | 0.5919 | 0.7693 |
| No log | 44.8571 | 314 | 0.5896 | 0.6625 | 0.5896 | 0.7679 |
| No log | 45.1429 | 316 | 0.5949 | 0.6625 | 0.5949 | 0.7713 |
| No log | 45.4286 | 318 | 0.6030 | 0.6593 | 0.6030 | 0.7765 |
| No log | 45.7143 | 320 | 0.6312 | 0.6099 | 0.6312 | 0.7945 |
| No log | 46.0 | 322 | 0.6583 | 0.5829 | 0.6583 | 0.8114 |
| No log | 46.2857 | 324 | 0.6592 | 0.5829 | 0.6592 | 0.8119 |
| No log | 46.5714 | 326 | 0.6496 | 0.6226 | 0.6496 | 0.8060 |
| No log | 46.8571 | 328 | 0.6236 | 0.6692 | 0.6236 | 0.7897 |
| No log | 47.1429 | 330 | 0.5921 | 0.6737 | 0.5921 | 0.7695 |
| No log | 47.4286 | 332 | 0.5845 | 0.6555 | 0.5845 | 0.7645 |
| No log | 47.7143 | 334 | 0.5839 | 0.6593 | 0.5839 | 0.7642 |
| No log | 48.0 | 336 | 0.5896 | 0.6787 | 0.5896 | 0.7678 |
| No log | 48.2857 | 338 | 0.5950 | 0.6787 | 0.5950 | 0.7714 |
| No log | 48.5714 | 340 | 0.6242 | 0.6803 | 0.6242 | 0.7900 |
| No log | 48.8571 | 342 | 0.6425 | 0.6411 | 0.6425 | 0.8016 |
| No log | 49.1429 | 344 | 0.6431 | 0.6970 | 0.6431 | 0.8020 |
| No log | 49.4286 | 346 | 0.6597 | 0.6729 | 0.6597 | 0.8122 |
| No log | 49.7143 | 348 | 0.6531 | 0.6970 | 0.6531 | 0.8082 |
| No log | 50.0 | 350 | 0.6106 | 0.6963 | 0.6106 | 0.7814 |
| No log | 50.2857 | 352 | 0.5964 | 0.6963 | 0.5964 | 0.7723 |
| No log | 50.5714 | 354 | 0.5933 | 0.6898 | 0.5933 | 0.7702 |
| No log | 50.8571 | 356 | 0.5880 | 0.6822 | 0.5880 | 0.7668 |
| No log | 51.1429 | 358 | 0.5849 | 0.6708 | 0.5849 | 0.7648 |
| No log | 51.4286 | 360 | 0.5778 | 0.6708 | 0.5778 | 0.7601 |
| No log | 51.7143 | 362 | 0.5896 | 0.6890 | 0.5896 | 0.7679 |
| No log | 52.0 | 364 | 0.5833 | 0.6890 | 0.5833 | 0.7638 |
| No log | 52.2857 | 366 | 0.5789 | 0.6778 | 0.5789 | 0.7608 |
| No log | 52.5714 | 368 | 0.5898 | 0.7064 | 0.5898 | 0.7680 |
| No log | 52.8571 | 370 | 0.6034 | 0.7064 | 0.6034 | 0.7768 |
| No log | 53.1429 | 372 | 0.6354 | 0.7071 | 0.6354 | 0.7971 |
| No log | 53.4286 | 374 | 0.6643 | 0.6090 | 0.6643 | 0.8150 |
| No log | 53.7143 | 376 | 0.6659 | 0.5898 | 0.6659 | 0.8160 |
| No log | 54.0 | 378 | 0.6531 | 0.5898 | 0.6531 | 0.8081 |
| No log | 54.2857 | 380 | 0.6213 | 0.7071 | 0.6213 | 0.7882 |
| No log | 54.5714 | 382 | 0.5905 | 0.7018 | 0.5905 | 0.7684 |
| No log | 54.8571 | 384 | 0.5759 | 0.6630 | 0.5759 | 0.7589 |
| No log | 55.1429 | 386 | 0.5795 | 0.6138 | 0.5795 | 0.7613 |
| No log | 55.4286 | 388 | 0.5763 | 0.6138 | 0.5763 | 0.7592 |
| No log | 55.7143 | 390 | 0.5700 | 0.5959 | 0.5700 | 0.7550 |
| No log | 56.0 | 392 | 0.5710 | 0.6555 | 0.5710 | 0.7557 |
| No log | 56.2857 | 394 | 0.5832 | 0.6854 | 0.5832 | 0.7637 |
| No log | 56.5714 | 396 | 0.5992 | 0.7071 | 0.5992 | 0.7741 |
| No log | 56.8571 | 398 | 0.5948 | 0.7071 | 0.5948 | 0.7712 |
| No log | 57.1429 | 400 | 0.5802 | 0.6737 | 0.5802 | 0.7617 |
| No log | 57.4286 | 402 | 0.5733 | 0.6306 | 0.5733 | 0.7571 |
| No log | 57.7143 | 404 | 0.5755 | 0.6509 | 0.5755 | 0.7586 |
| No log | 58.0 | 406 | 0.5718 | 0.6330 | 0.5718 | 0.7562 |
| No log | 58.2857 | 408 | 0.5658 | 0.6584 | 0.5658 | 0.7522 |
| No log | 58.5714 | 410 | 0.5659 | 0.6625 | 0.5659 | 0.7522 |
| No log | 58.8571 | 412 | 0.5729 | 0.6708 | 0.5729 | 0.7569 |
| No log | 59.1429 | 414 | 0.5863 | 0.7071 | 0.5863 | 0.7657 |
| No log | 59.4286 | 416 | 0.5998 | 0.6779 | 0.5998 | 0.7744 |
| No log | 59.7143 | 418 | 0.6092 | 0.6779 | 0.6092 | 0.7805 |
| No log | 60.0 | 420 | 0.6163 | 0.6779 | 0.6163 | 0.7850 |
| No log | 60.2857 | 422 | 0.6161 | 0.6779 | 0.6161 | 0.7849 |
| No log | 60.5714 | 424 | 0.6026 | 0.6675 | 0.6026 | 0.7763 |
| No log | 60.8571 | 426 | 0.5870 | 0.6535 | 0.5870 | 0.7662 |
| No log | 61.1429 | 428 | 0.5772 | 0.6659 | 0.5772 | 0.7598 |
| No log | 61.4286 | 430 | 0.5671 | 0.6586 | 0.5671 | 0.7531 |
| No log | 61.7143 | 432 | 0.5587 | 0.6111 | 0.5587 | 0.7475 |
| No log | 62.0 | 434 | 0.5542 | 0.6447 | 0.5542 | 0.7444 |
| No log | 62.2857 | 436 | 0.5570 | 0.6555 | 0.5570 | 0.7464 |
| No log | 62.5714 | 438 | 0.5668 | 0.6787 | 0.5668 | 0.7529 |
| No log | 62.8571 | 440 | 0.5884 | 0.7071 | 0.5884 | 0.7671 |
| No log | 63.1429 | 442 | 0.6258 | 0.7071 | 0.6258 | 0.7911 |
| No log | 63.4286 | 444 | 0.6430 | 0.7071 | 0.6430 | 0.8019 |
| No log | 63.7143 | 446 | 0.6339 | 0.7071 | 0.6339 | 0.7962 |
| No log | 64.0 | 448 | 0.6109 | 0.6919 | 0.6109 | 0.7816 |
| No log | 64.2857 | 450 | 0.6049 | 0.6594 | 0.6049 | 0.7778 |
| No log | 64.5714 | 452 | 0.6036 | 0.6594 | 0.6036 | 0.7769 |
| No log | 64.8571 | 454 | 0.6000 | 0.6594 | 0.6000 | 0.7746 |
| No log | 65.1429 | 456 | 0.5970 | 0.6535 | 0.5970 | 0.7727 |
| No log | 65.4286 | 458 | 0.6014 | 0.6963 | 0.6014 | 0.7755 |
| No log | 65.7143 | 460 | 0.5990 | 0.6787 | 0.5990 | 0.7740 |
| No log | 66.0 | 462 | 0.5952 | 0.6787 | 0.5952 | 0.7715 |
| No log | 66.2857 | 464 | 0.5942 | 0.6898 | 0.5942 | 0.7708 |
| No log | 66.5714 | 466 | 0.5974 | 0.7071 | 0.5974 | 0.7729 |
| No log | 66.8571 | 468 | 0.6068 | 0.7071 | 0.6068 | 0.7790 |
| No log | 67.1429 | 470 | 0.6143 | 0.7071 | 0.6143 | 0.7838 |
| No log | 67.4286 | 472 | 0.6248 | 0.6661 | 0.6248 | 0.7905 |
| No log | 67.7143 | 474 | 0.6320 | 0.6661 | 0.6320 | 0.7950 |
| No log | 68.0 | 476 | 0.6427 | 0.6661 | 0.6427 | 0.8017 |
| No log | 68.2857 | 478 | 0.6259 | 0.6761 | 0.6259 | 0.7911 |
| No log | 68.5714 | 480 | 0.6090 | 0.7071 | 0.6090 | 0.7804 |
| No log | 68.8571 | 482 | 0.6037 | 0.7025 | 0.6037 | 0.7770 |
| No log | 69.1429 | 484 | 0.6037 | 0.7025 | 0.6037 | 0.7770 |
| No log | 69.4286 | 486 | 0.6089 | 0.7025 | 0.6089 | 0.7803 |
| No log | 69.7143 | 488 | 0.6172 | 0.6981 | 0.6172 | 0.7856 |
| No log | 70.0 | 490 | 0.6264 | 0.7025 | 0.6264 | 0.7915 |
| No log | 70.2857 | 492 | 0.6326 | 0.7025 | 0.6326 | 0.7954 |
| No log | 70.5714 | 494 | 0.6442 | 0.6988 | 0.6442 | 0.8026 |
| No log | 70.8571 | 496 | 0.6461 | 0.6988 | 0.6461 | 0.8038 |
| No log | 71.1429 | 498 | 0.6484 | 0.6988 | 0.6484 | 0.8052 |
| 0.2224 | 71.4286 | 500 | 0.6411 | 0.6988 | 0.6411 | 0.8007 |
| 0.2224 | 71.7143 | 502 | 0.6367 | 0.7025 | 0.6367 | 0.7979 |
| 0.2224 | 72.0 | 504 | 0.6345 | 0.7071 | 0.6345 | 0.7965 |
| 0.2224 | 72.2857 | 506 | 0.6356 | 0.7071 | 0.6356 | 0.7972 |
| 0.2224 | 72.5714 | 508 | 0.6353 | 0.7071 | 0.6353 | 0.7971 |
| 0.2224 | 72.8571 | 510 | 0.6337 | 0.7071 | 0.6337 | 0.7961 |
| 0.2224 | 73.1429 | 512 | 0.6443 | 0.7071 | 0.6443 | 0.8027 |
| 0.2224 | 73.4286 | 514 | 0.6348 | 0.7071 | 0.6348 | 0.7968 |
| 0.2224 | 73.7143 | 516 | 0.6133 | 0.7071 | 0.6133 | 0.7831 |
| 0.2224 | 74.0 | 518 | 0.5929 | 0.6708 | 0.5929 | 0.7700 |
| 0.2224 | 74.2857 | 520 | 0.5844 | 0.6742 | 0.5844 | 0.7645 |
| 0.2224 | 74.5714 | 522 | 0.5831 | 0.6742 | 0.5831 | 0.7636 |
| 0.2224 | 74.8571 | 524 | 0.5850 | 0.6742 | 0.5850 | 0.7649 |
| 0.2224 | 75.1429 | 526 | 0.5891 | 0.6742 | 0.5891 | 0.7675 |
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/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k1_task5_organization
Base model
aubmindlab/bert-base-arabertv02