Instructions to use MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k15_task2_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: 0.6459
- Qwk: 0.3898
- Mse: 0.6459
- Rmse: 0.8037
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 | 0.0253 | 2 | 4.2505 | -0.0177 | 4.2505 | 2.0617 |
| No log | 0.0506 | 4 | 2.2184 | 0.0142 | 2.2184 | 1.4894 |
| No log | 0.0759 | 6 | 1.7451 | 0.0242 | 1.7451 | 1.3210 |
| No log | 0.1013 | 8 | 1.9089 | -0.0059 | 1.9089 | 1.3816 |
| No log | 0.1266 | 10 | 1.3109 | -0.0156 | 1.3109 | 1.1449 |
| No log | 0.1519 | 12 | 1.0637 | -0.0192 | 1.0637 | 1.0313 |
| No log | 0.1772 | 14 | 0.9276 | 0.0975 | 0.9276 | 0.9631 |
| No log | 0.2025 | 16 | 0.9180 | 0.0917 | 0.9180 | 0.9581 |
| No log | 0.2278 | 18 | 0.8450 | 0.1624 | 0.8450 | 0.9192 |
| No log | 0.2532 | 20 | 0.8357 | 0.1080 | 0.8357 | 0.9142 |
| No log | 0.2785 | 22 | 0.9274 | 0.1451 | 0.9274 | 0.9630 |
| No log | 0.3038 | 24 | 1.1486 | -0.0890 | 1.1486 | 1.0717 |
| No log | 0.3291 | 26 | 0.9458 | 0.0412 | 0.9458 | 0.9725 |
| No log | 0.3544 | 28 | 0.8251 | 0.0443 | 0.8251 | 0.9083 |
| No log | 0.3797 | 30 | 0.7956 | 0.1424 | 0.7956 | 0.8920 |
| No log | 0.4051 | 32 | 0.8021 | 0.1489 | 0.8021 | 0.8956 |
| No log | 0.4304 | 34 | 0.8089 | 0.1481 | 0.8089 | 0.8994 |
| No log | 0.4557 | 36 | 0.8070 | 0.2167 | 0.8070 | 0.8983 |
| No log | 0.4810 | 38 | 0.8158 | 0.1946 | 0.8158 | 0.9032 |
| No log | 0.5063 | 40 | 0.8861 | 0.1742 | 0.8861 | 0.9413 |
| No log | 0.5316 | 42 | 0.9924 | 0.0018 | 0.9924 | 0.9962 |
| No log | 0.5570 | 44 | 1.0619 | 0.0313 | 1.0619 | 1.0305 |
| No log | 0.5823 | 46 | 1.1678 | 0.0210 | 1.1678 | 1.0806 |
| No log | 0.6076 | 48 | 1.3421 | -0.0050 | 1.3421 | 1.1585 |
| No log | 0.6329 | 50 | 1.2695 | 0.0 | 1.2695 | 1.1267 |
| No log | 0.6582 | 52 | 1.0293 | 0.0955 | 1.0293 | 1.0145 |
| No log | 0.6835 | 54 | 0.8045 | 0.2548 | 0.8045 | 0.8969 |
| No log | 0.7089 | 56 | 0.7360 | 0.2813 | 0.7360 | 0.8579 |
| No log | 0.7342 | 58 | 0.7251 | 0.2414 | 0.7251 | 0.8515 |
| No log | 0.7595 | 60 | 0.7353 | 0.2524 | 0.7353 | 0.8575 |
| No log | 0.7848 | 62 | 0.7814 | 0.2772 | 0.7814 | 0.8840 |
| No log | 0.8101 | 64 | 0.8209 | 0.3074 | 0.8209 | 0.9060 |
| No log | 0.8354 | 66 | 0.7989 | 0.3292 | 0.7989 | 0.8938 |
| No log | 0.8608 | 68 | 0.7318 | 0.3120 | 0.7318 | 0.8554 |
| No log | 0.8861 | 70 | 0.7017 | 0.2849 | 0.7017 | 0.8377 |
| No log | 0.9114 | 72 | 0.6996 | 0.1769 | 0.6996 | 0.8364 |
| No log | 0.9367 | 74 | 0.6678 | 0.3208 | 0.6678 | 0.8172 |
| No log | 0.9620 | 76 | 0.6464 | 0.3205 | 0.6464 | 0.8040 |
| No log | 0.9873 | 78 | 0.6497 | 0.3530 | 0.6497 | 0.8060 |
| No log | 1.0127 | 80 | 0.6705 | 0.3437 | 0.6705 | 0.8188 |
| No log | 1.0380 | 82 | 0.6468 | 0.3750 | 0.6468 | 0.8043 |
| No log | 1.0633 | 84 | 0.6282 | 0.4059 | 0.6282 | 0.7926 |
| No log | 1.0886 | 86 | 0.6661 | 0.4174 | 0.6661 | 0.8161 |
| No log | 1.1139 | 88 | 0.6535 | 0.4468 | 0.6535 | 0.8084 |
| No log | 1.1392 | 90 | 0.7523 | 0.2194 | 0.7523 | 0.8673 |
| No log | 1.1646 | 92 | 1.0431 | -0.0698 | 1.0431 | 1.0213 |
| No log | 1.1899 | 94 | 0.9895 | 0.0043 | 0.9895 | 0.9948 |
| No log | 1.2152 | 96 | 0.8580 | 0.1110 | 0.8580 | 0.9263 |
| No log | 1.2405 | 98 | 0.7941 | 0.0637 | 0.7941 | 0.8912 |
| No log | 1.2658 | 100 | 0.8263 | 0.1197 | 0.8263 | 0.9090 |
| No log | 1.2911 | 102 | 0.7835 | 0.3014 | 0.7835 | 0.8852 |
| No log | 1.3165 | 104 | 0.7562 | 0.4080 | 0.7562 | 0.8696 |
| No log | 1.3418 | 106 | 0.8323 | 0.4275 | 0.8323 | 0.9123 |
| No log | 1.3671 | 108 | 0.8625 | 0.4370 | 0.8625 | 0.9287 |
| No log | 1.3924 | 110 | 0.8483 | 0.4085 | 0.8483 | 0.9210 |
| No log | 1.4177 | 112 | 0.9687 | 0.3943 | 0.9687 | 0.9842 |
| No log | 1.4430 | 114 | 0.8825 | 0.3044 | 0.8825 | 0.9394 |
| No log | 1.4684 | 116 | 0.7950 | 0.3398 | 0.7950 | 0.8916 |
| No log | 1.4937 | 118 | 0.6877 | 0.4506 | 0.6877 | 0.8293 |
| No log | 1.5190 | 120 | 0.7292 | 0.4294 | 0.7292 | 0.8539 |
| No log | 1.5443 | 122 | 0.9745 | 0.3941 | 0.9745 | 0.9872 |
| No log | 1.5696 | 124 | 1.2930 | 0.2209 | 1.2930 | 1.1371 |
| No log | 1.5949 | 126 | 1.2283 | 0.2574 | 1.2283 | 1.1083 |
| No log | 1.6203 | 128 | 0.9029 | 0.3806 | 0.9029 | 0.9502 |
| No log | 1.6456 | 130 | 0.7345 | 0.3609 | 0.7345 | 0.8570 |
| No log | 1.6709 | 132 | 0.6275 | 0.4214 | 0.6275 | 0.7922 |
| No log | 1.6962 | 134 | 0.6533 | 0.4112 | 0.6533 | 0.8083 |
| No log | 1.7215 | 136 | 0.7564 | 0.3767 | 0.7564 | 0.8697 |
| No log | 1.7468 | 138 | 0.7648 | 0.3556 | 0.7648 | 0.8746 |
| No log | 1.7722 | 140 | 0.6834 | 0.5026 | 0.6834 | 0.8267 |
| No log | 1.7975 | 142 | 0.6698 | 0.5076 | 0.6698 | 0.8184 |
| No log | 1.8228 | 144 | 0.6559 | 0.4448 | 0.6559 | 0.8099 |
| No log | 1.8481 | 146 | 0.6240 | 0.5152 | 0.6240 | 0.7900 |
| No log | 1.8734 | 148 | 0.6290 | 0.4180 | 0.6290 | 0.7931 |
| No log | 1.8987 | 150 | 0.7239 | 0.3253 | 0.7239 | 0.8508 |
| No log | 1.9241 | 152 | 0.7014 | 0.2744 | 0.7014 | 0.8375 |
| No log | 1.9494 | 154 | 0.6275 | 0.4596 | 0.6275 | 0.7921 |
| No log | 1.9747 | 156 | 0.6436 | 0.4999 | 0.6436 | 0.8022 |
| No log | 2.0 | 158 | 0.7022 | 0.4602 | 0.7022 | 0.8380 |
| No log | 2.0253 | 160 | 0.7540 | 0.4122 | 0.7540 | 0.8683 |
| No log | 2.0506 | 162 | 0.8188 | 0.4202 | 0.8188 | 0.9049 |
| No log | 2.0759 | 164 | 0.8403 | 0.4024 | 0.8403 | 0.9167 |
| No log | 2.1013 | 166 | 0.7284 | 0.3354 | 0.7284 | 0.8535 |
| No log | 2.1266 | 168 | 0.6299 | 0.3553 | 0.6299 | 0.7936 |
| No log | 2.1519 | 170 | 0.6011 | 0.3937 | 0.6011 | 0.7753 |
| No log | 2.1772 | 172 | 0.6277 | 0.4596 | 0.6277 | 0.7922 |
| No log | 2.2025 | 174 | 0.6054 | 0.4116 | 0.6054 | 0.7780 |
| No log | 2.2278 | 176 | 0.6781 | 0.3873 | 0.6781 | 0.8235 |
| No log | 2.2532 | 178 | 0.7561 | 0.4028 | 0.7561 | 0.8695 |
| No log | 2.2785 | 180 | 0.6803 | 0.4508 | 0.6803 | 0.8248 |
| No log | 2.3038 | 182 | 0.6195 | 0.4894 | 0.6195 | 0.7871 |
| No log | 2.3291 | 184 | 0.6331 | 0.4887 | 0.6331 | 0.7957 |
| No log | 2.3544 | 186 | 0.7743 | 0.3891 | 0.7743 | 0.8799 |
| No log | 2.3797 | 188 | 0.8037 | 0.4294 | 0.8037 | 0.8965 |
| No log | 2.4051 | 190 | 0.6655 | 0.3865 | 0.6655 | 0.8158 |
| No log | 2.4304 | 192 | 0.5837 | 0.5187 | 0.5837 | 0.7640 |
| No log | 2.4557 | 194 | 0.5865 | 0.4817 | 0.5865 | 0.7658 |
| No log | 2.4810 | 196 | 0.6494 | 0.4179 | 0.6494 | 0.8059 |
| No log | 2.5063 | 198 | 0.6518 | 0.4537 | 0.6518 | 0.8073 |
| No log | 2.5316 | 200 | 0.6562 | 0.4559 | 0.6562 | 0.8101 |
| No log | 2.5570 | 202 | 0.5919 | 0.5188 | 0.5919 | 0.7693 |
| No log | 2.5823 | 204 | 0.5892 | 0.5259 | 0.5892 | 0.7676 |
| No log | 2.6076 | 206 | 0.5985 | 0.5180 | 0.5985 | 0.7736 |
| No log | 2.6329 | 208 | 0.7197 | 0.4238 | 0.7197 | 0.8483 |
| No log | 2.6582 | 210 | 0.7102 | 0.4010 | 0.7102 | 0.8427 |
| No log | 2.6835 | 212 | 0.5844 | 0.4379 | 0.5844 | 0.7645 |
| No log | 2.7089 | 214 | 0.5834 | 0.5119 | 0.5834 | 0.7638 |
| No log | 2.7342 | 216 | 0.5756 | 0.4353 | 0.5756 | 0.7587 |
| No log | 2.7595 | 218 | 0.6724 | 0.3804 | 0.6724 | 0.8200 |
| No log | 2.7848 | 220 | 0.8677 | 0.3999 | 0.8677 | 0.9315 |
| No log | 2.8101 | 222 | 0.8294 | 0.3718 | 0.8294 | 0.9107 |
| No log | 2.8354 | 224 | 0.6275 | 0.4156 | 0.6275 | 0.7922 |
| No log | 2.8608 | 226 | 0.5429 | 0.5085 | 0.5429 | 0.7368 |
| No log | 2.8861 | 228 | 0.6083 | 0.5511 | 0.6083 | 0.7800 |
| No log | 2.9114 | 230 | 0.5705 | 0.5671 | 0.5705 | 0.7553 |
| No log | 2.9367 | 232 | 0.5490 | 0.5256 | 0.5490 | 0.7410 |
| No log | 2.9620 | 234 | 0.5470 | 0.5110 | 0.5470 | 0.7396 |
| No log | 2.9873 | 236 | 0.5513 | 0.5101 | 0.5513 | 0.7425 |
| No log | 3.0127 | 238 | 0.5477 | 0.4917 | 0.5477 | 0.7400 |
| No log | 3.0380 | 240 | 0.5594 | 0.5442 | 0.5594 | 0.7479 |
| No log | 3.0633 | 242 | 0.5523 | 0.5140 | 0.5523 | 0.7432 |
| No log | 3.0886 | 244 | 0.5954 | 0.5444 | 0.5954 | 0.7716 |
| No log | 3.1139 | 246 | 0.5929 | 0.5444 | 0.5929 | 0.7700 |
| No log | 3.1392 | 248 | 0.5433 | 0.5297 | 0.5433 | 0.7371 |
| No log | 3.1646 | 250 | 0.5981 | 0.4695 | 0.5981 | 0.7734 |
| No log | 3.1899 | 252 | 0.6178 | 0.4634 | 0.6178 | 0.7860 |
| No log | 3.2152 | 254 | 0.5808 | 0.5371 | 0.5808 | 0.7621 |
| No log | 3.2405 | 256 | 0.5507 | 0.5377 | 0.5507 | 0.7421 |
| No log | 3.2658 | 258 | 0.5531 | 0.5288 | 0.5531 | 0.7437 |
| No log | 3.2911 | 260 | 0.5611 | 0.5013 | 0.5611 | 0.7491 |
| No log | 3.3165 | 262 | 0.6085 | 0.5118 | 0.6085 | 0.7801 |
| No log | 3.3418 | 264 | 0.6230 | 0.4508 | 0.6230 | 0.7893 |
| No log | 3.3671 | 266 | 0.5790 | 0.4588 | 0.5790 | 0.7609 |
| No log | 3.3924 | 268 | 0.5569 | 0.4633 | 0.5569 | 0.7462 |
| No log | 3.4177 | 270 | 0.5581 | 0.4596 | 0.5581 | 0.7471 |
| No log | 3.4430 | 272 | 0.5568 | 0.4751 | 0.5568 | 0.7462 |
| No log | 3.4684 | 274 | 0.5837 | 0.4913 | 0.5837 | 0.7640 |
| No log | 3.4937 | 276 | 0.6994 | 0.3483 | 0.6994 | 0.8363 |
| No log | 3.5190 | 278 | 0.6883 | 0.3718 | 0.6883 | 0.8296 |
| No log | 3.5443 | 280 | 0.5759 | 0.5015 | 0.5759 | 0.7589 |
| No log | 3.5696 | 282 | 0.5962 | 0.5334 | 0.5962 | 0.7722 |
| No log | 3.5949 | 284 | 0.7513 | 0.4057 | 0.7513 | 0.8668 |
| No log | 3.6203 | 286 | 0.7169 | 0.4118 | 0.7169 | 0.8467 |
| No log | 3.6456 | 288 | 0.5683 | 0.5079 | 0.5683 | 0.7538 |
| No log | 3.6709 | 290 | 0.5738 | 0.4944 | 0.5738 | 0.7575 |
| No log | 3.6962 | 292 | 0.6480 | 0.4690 | 0.6480 | 0.8050 |
| No log | 3.7215 | 294 | 0.6651 | 0.4516 | 0.6651 | 0.8156 |
| No log | 3.7468 | 296 | 0.5962 | 0.5080 | 0.5962 | 0.7721 |
| No log | 3.7722 | 298 | 0.5630 | 0.5106 | 0.5630 | 0.7503 |
| No log | 3.7975 | 300 | 0.5563 | 0.4587 | 0.5563 | 0.7458 |
| No log | 3.8228 | 302 | 0.5598 | 0.4265 | 0.5598 | 0.7482 |
| No log | 3.8481 | 304 | 0.5694 | 0.4576 | 0.5694 | 0.7546 |
| No log | 3.8734 | 306 | 0.5578 | 0.4168 | 0.5578 | 0.7469 |
| No log | 3.8987 | 308 | 0.5465 | 0.4767 | 0.5465 | 0.7392 |
| No log | 3.9241 | 310 | 0.5736 | 0.5186 | 0.5736 | 0.7573 |
| No log | 3.9494 | 312 | 0.5897 | 0.4701 | 0.5897 | 0.7679 |
| No log | 3.9747 | 314 | 0.5464 | 0.5484 | 0.5464 | 0.7392 |
| No log | 4.0 | 316 | 0.5712 | 0.5227 | 0.5712 | 0.7558 |
| No log | 4.0253 | 318 | 0.5737 | 0.5227 | 0.5737 | 0.7575 |
| No log | 4.0506 | 320 | 0.5493 | 0.5739 | 0.5493 | 0.7411 |
| No log | 4.0759 | 322 | 0.5579 | 0.5830 | 0.5579 | 0.7469 |
| No log | 4.1013 | 324 | 0.5569 | 0.5589 | 0.5569 | 0.7462 |
| No log | 4.1266 | 326 | 0.6217 | 0.5250 | 0.6217 | 0.7885 |
| No log | 4.1519 | 328 | 0.7154 | 0.4807 | 0.7154 | 0.8458 |
| No log | 4.1772 | 330 | 0.6870 | 0.4561 | 0.6870 | 0.8288 |
| No log | 4.2025 | 332 | 0.5822 | 0.4916 | 0.5822 | 0.7630 |
| No log | 4.2278 | 334 | 0.5483 | 0.4600 | 0.5483 | 0.7405 |
| No log | 4.2532 | 336 | 0.5495 | 0.5058 | 0.5495 | 0.7413 |
| No log | 4.2785 | 338 | 0.5584 | 0.5105 | 0.5584 | 0.7472 |
| No log | 4.3038 | 340 | 0.5841 | 0.4863 | 0.5841 | 0.7643 |
| No log | 4.3291 | 342 | 0.6149 | 0.5227 | 0.6149 | 0.7841 |
| No log | 4.3544 | 344 | 0.6320 | 0.5339 | 0.6320 | 0.7950 |
| No log | 4.3797 | 346 | 0.5791 | 0.5021 | 0.5791 | 0.7610 |
| No log | 4.4051 | 348 | 0.5831 | 0.5319 | 0.5831 | 0.7636 |
| No log | 4.4304 | 350 | 0.6359 | 0.5348 | 0.6359 | 0.7975 |
| No log | 4.4557 | 352 | 0.6198 | 0.5348 | 0.6198 | 0.7873 |
| No log | 4.4810 | 354 | 0.5747 | 0.4985 | 0.5747 | 0.7581 |
| No log | 4.5063 | 356 | 0.5520 | 0.4700 | 0.5520 | 0.7430 |
| No log | 4.5316 | 358 | 0.5573 | 0.4600 | 0.5573 | 0.7465 |
| No log | 4.5570 | 360 | 0.6092 | 0.4654 | 0.6092 | 0.7805 |
| No log | 4.5823 | 362 | 0.6252 | 0.4585 | 0.6252 | 0.7907 |
| No log | 4.6076 | 364 | 0.5555 | 0.5006 | 0.5555 | 0.7453 |
| No log | 4.6329 | 366 | 0.5390 | 0.5239 | 0.5390 | 0.7342 |
| No log | 4.6582 | 368 | 0.5788 | 0.5556 | 0.5788 | 0.7608 |
| No log | 4.6835 | 370 | 0.5607 | 0.5687 | 0.5607 | 0.7488 |
| No log | 4.7089 | 372 | 0.5579 | 0.4925 | 0.5579 | 0.7469 |
| No log | 4.7342 | 374 | 0.6041 | 0.4291 | 0.6041 | 0.7772 |
| No log | 4.7595 | 376 | 0.5787 | 0.3578 | 0.5787 | 0.7607 |
| No log | 4.7848 | 378 | 0.5760 | 0.3738 | 0.5760 | 0.7589 |
| No log | 4.8101 | 380 | 0.5720 | 0.3720 | 0.5720 | 0.7563 |
| No log | 4.8354 | 382 | 0.5620 | 0.4976 | 0.5620 | 0.7497 |
| No log | 4.8608 | 384 | 0.5755 | 0.5598 | 0.5755 | 0.7586 |
| No log | 4.8861 | 386 | 0.5866 | 0.5554 | 0.5866 | 0.7659 |
| No log | 4.9114 | 388 | 0.5664 | 0.5428 | 0.5664 | 0.7526 |
| No log | 4.9367 | 390 | 0.5820 | 0.4627 | 0.5820 | 0.7629 |
| No log | 4.9620 | 392 | 0.5756 | 0.3987 | 0.5756 | 0.7587 |
| No log | 4.9873 | 394 | 0.5576 | 0.4617 | 0.5576 | 0.7467 |
| No log | 5.0127 | 396 | 0.5580 | 0.4235 | 0.5580 | 0.7470 |
| No log | 5.0380 | 398 | 0.5565 | 0.4741 | 0.5565 | 0.7460 |
| No log | 5.0633 | 400 | 0.5467 | 0.5120 | 0.5467 | 0.7394 |
| No log | 5.0886 | 402 | 0.5492 | 0.5081 | 0.5492 | 0.7411 |
| No log | 5.1139 | 404 | 0.5476 | 0.4865 | 0.5476 | 0.7400 |
| No log | 5.1392 | 406 | 0.5504 | 0.5201 | 0.5504 | 0.7419 |
| No log | 5.1646 | 408 | 0.5681 | 0.4364 | 0.5681 | 0.7537 |
| No log | 5.1899 | 410 | 0.6008 | 0.4541 | 0.6008 | 0.7751 |
| No log | 5.2152 | 412 | 0.5824 | 0.4218 | 0.5824 | 0.7631 |
| No log | 5.2405 | 414 | 0.5604 | 0.4515 | 0.5604 | 0.7486 |
| No log | 5.2658 | 416 | 0.5587 | 0.5036 | 0.5587 | 0.7475 |
| No log | 5.2911 | 418 | 0.5671 | 0.4398 | 0.5671 | 0.7531 |
| No log | 5.3165 | 420 | 0.5886 | 0.4482 | 0.5886 | 0.7672 |
| No log | 5.3418 | 422 | 0.5706 | 0.4710 | 0.5706 | 0.7554 |
| No log | 5.3671 | 424 | 0.5613 | 0.4850 | 0.5613 | 0.7492 |
| No log | 5.3924 | 426 | 0.5568 | 0.4850 | 0.5568 | 0.7462 |
| No log | 5.4177 | 428 | 0.5525 | 0.5215 | 0.5525 | 0.7433 |
| No log | 5.4430 | 430 | 0.5810 | 0.5194 | 0.5810 | 0.7623 |
| No log | 5.4684 | 432 | 0.6813 | 0.4671 | 0.6813 | 0.8254 |
| No log | 5.4937 | 434 | 0.7669 | 0.3783 | 0.7669 | 0.8757 |
| No log | 5.5190 | 436 | 0.7053 | 0.3749 | 0.7053 | 0.8398 |
| No log | 5.5443 | 438 | 0.6118 | 0.4484 | 0.6118 | 0.7822 |
| No log | 5.5696 | 440 | 0.5744 | 0.4700 | 0.5744 | 0.7579 |
| No log | 5.5949 | 442 | 0.5826 | 0.4499 | 0.5826 | 0.7633 |
| No log | 5.6203 | 444 | 0.6455 | 0.4253 | 0.6455 | 0.8034 |
| No log | 5.6456 | 446 | 0.7571 | 0.3834 | 0.7571 | 0.8701 |
| No log | 5.6709 | 448 | 0.7623 | 0.3922 | 0.7623 | 0.8731 |
| No log | 5.6962 | 450 | 0.6810 | 0.4671 | 0.6810 | 0.8252 |
| No log | 5.7215 | 452 | 0.6125 | 0.4370 | 0.6125 | 0.7826 |
| No log | 5.7468 | 454 | 0.5767 | 0.5099 | 0.5767 | 0.7594 |
| No log | 5.7722 | 456 | 0.5874 | 0.4599 | 0.5874 | 0.7664 |
| No log | 5.7975 | 458 | 0.6369 | 0.4948 | 0.6369 | 0.7981 |
| No log | 5.8228 | 460 | 0.7443 | 0.4657 | 0.7443 | 0.8627 |
| No log | 5.8481 | 462 | 0.7319 | 0.4683 | 0.7319 | 0.8555 |
| No log | 5.8734 | 464 | 0.6681 | 0.4662 | 0.6681 | 0.8174 |
| No log | 5.8987 | 466 | 0.6153 | 0.4853 | 0.6153 | 0.7844 |
| No log | 5.9241 | 468 | 0.5661 | 0.5123 | 0.5661 | 0.7524 |
| No log | 5.9494 | 470 | 0.5766 | 0.5481 | 0.5766 | 0.7593 |
| No log | 5.9747 | 472 | 0.6359 | 0.5278 | 0.6359 | 0.7974 |
| No log | 6.0 | 474 | 0.7182 | 0.4803 | 0.7182 | 0.8474 |
| No log | 6.0253 | 476 | 0.7125 | 0.4822 | 0.7125 | 0.8441 |
| No log | 6.0506 | 478 | 0.5931 | 0.5475 | 0.5931 | 0.7702 |
| No log | 6.0759 | 480 | 0.5384 | 0.5629 | 0.5384 | 0.7338 |
| No log | 6.1013 | 482 | 0.5340 | 0.5743 | 0.5340 | 0.7307 |
| No log | 6.1266 | 484 | 0.5449 | 0.4903 | 0.5449 | 0.7382 |
| No log | 6.1519 | 486 | 0.6444 | 0.4994 | 0.6444 | 0.8027 |
| No log | 6.1772 | 488 | 0.7057 | 0.4834 | 0.7057 | 0.8400 |
| No log | 6.2025 | 490 | 0.6356 | 0.4620 | 0.6356 | 0.7972 |
| No log | 6.2278 | 492 | 0.5477 | 0.5065 | 0.5477 | 0.7401 |
| No log | 6.2532 | 494 | 0.5336 | 0.5229 | 0.5336 | 0.7305 |
| No log | 6.2785 | 496 | 0.5492 | 0.4969 | 0.5492 | 0.7411 |
| No log | 6.3038 | 498 | 0.5895 | 0.4914 | 0.5895 | 0.7678 |
| 0.4118 | 6.3291 | 500 | 0.6250 | 0.4729 | 0.6250 | 0.7906 |
| 0.4118 | 6.3544 | 502 | 0.6249 | 0.4729 | 0.6249 | 0.7905 |
| 0.4118 | 6.3797 | 504 | 0.6089 | 0.4668 | 0.6089 | 0.7803 |
| 0.4118 | 6.4051 | 506 | 0.6500 | 0.4316 | 0.6500 | 0.8062 |
| 0.4118 | 6.4304 | 508 | 0.6437 | 0.4140 | 0.6437 | 0.8023 |
| 0.4118 | 6.4557 | 510 | 0.6459 | 0.3898 | 0.6459 | 0.8037 |
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/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k15_task2_organization
Base model
aubmindlab/bert-base-arabertv02