Instructions to use MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k16_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_k16_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_k16_task5_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k16_task5_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k16_task5_organization") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits7_B_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k16_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: 0.6342
- Qwk: 0.6063
- Mse: 0.6342
- Rmse: 0.7963
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 | 0.0247 | 2 | 4.1384 | 0.0024 | 4.1384 | 2.0343 |
| No log | 0.0494 | 4 | 2.4671 | 0.0215 | 2.4671 | 1.5707 |
| No log | 0.0741 | 6 | 1.5864 | -0.0180 | 1.5864 | 1.2595 |
| No log | 0.0988 | 8 | 1.1625 | 0.1752 | 1.1625 | 1.0782 |
| No log | 0.1235 | 10 | 1.1253 | 0.2291 | 1.1253 | 1.0608 |
| No log | 0.1481 | 12 | 1.1946 | 0.2391 | 1.1946 | 1.0930 |
| No log | 0.1728 | 14 | 1.5168 | -0.0245 | 1.5168 | 1.2316 |
| No log | 0.1975 | 16 | 1.5284 | -0.0064 | 1.5284 | 1.2363 |
| No log | 0.2222 | 18 | 1.2105 | 0.1767 | 1.2105 | 1.1002 |
| No log | 0.2469 | 20 | 1.1202 | 0.1810 | 1.1202 | 1.0584 |
| No log | 0.2716 | 22 | 1.0973 | 0.1848 | 1.0973 | 1.0475 |
| No log | 0.2963 | 24 | 1.1401 | 0.0790 | 1.1401 | 1.0678 |
| No log | 0.3210 | 26 | 1.2429 | 0.0849 | 1.2429 | 1.1148 |
| No log | 0.3457 | 28 | 1.4109 | 0.0380 | 1.4109 | 1.1878 |
| No log | 0.3704 | 30 | 1.3037 | 0.0349 | 1.3037 | 1.1418 |
| No log | 0.3951 | 32 | 1.2103 | 0.1086 | 1.2103 | 1.1002 |
| No log | 0.4198 | 34 | 1.0631 | 0.2615 | 1.0631 | 1.0311 |
| No log | 0.4444 | 36 | 1.1055 | 0.1873 | 1.1055 | 1.0514 |
| No log | 0.4691 | 38 | 1.1906 | 0.2089 | 1.1906 | 1.0912 |
| No log | 0.4938 | 40 | 1.2238 | 0.1700 | 1.2238 | 1.1062 |
| No log | 0.5185 | 42 | 1.1803 | 0.2424 | 1.1803 | 1.0864 |
| No log | 0.5432 | 44 | 1.0405 | 0.2325 | 1.0405 | 1.0201 |
| No log | 0.5679 | 46 | 0.9891 | 0.3280 | 0.9891 | 0.9946 |
| No log | 0.5926 | 48 | 0.9510 | 0.3425 | 0.9510 | 0.9752 |
| No log | 0.6173 | 50 | 0.9165 | 0.3857 | 0.9165 | 0.9573 |
| No log | 0.6420 | 52 | 0.9469 | 0.2782 | 0.9469 | 0.9731 |
| No log | 0.6667 | 54 | 0.9194 | 0.3671 | 0.9194 | 0.9589 |
| No log | 0.6914 | 56 | 0.8581 | 0.4551 | 0.8581 | 0.9263 |
| No log | 0.7160 | 58 | 0.8494 | 0.3942 | 0.8494 | 0.9216 |
| No log | 0.7407 | 60 | 0.8521 | 0.4608 | 0.8521 | 0.9231 |
| No log | 0.7654 | 62 | 0.8365 | 0.4764 | 0.8365 | 0.9146 |
| No log | 0.7901 | 64 | 0.8461 | 0.3543 | 0.8461 | 0.9198 |
| No log | 0.8148 | 66 | 0.9487 | 0.3041 | 0.9487 | 0.9740 |
| No log | 0.8395 | 68 | 0.8904 | 0.2499 | 0.8904 | 0.9436 |
| No log | 0.8642 | 70 | 0.7665 | 0.4919 | 0.7665 | 0.8755 |
| No log | 0.8889 | 72 | 0.9275 | 0.3935 | 0.9275 | 0.9631 |
| No log | 0.9136 | 74 | 0.9855 | 0.3935 | 0.9855 | 0.9927 |
| No log | 0.9383 | 76 | 0.9290 | 0.3291 | 0.9290 | 0.9639 |
| No log | 0.9630 | 78 | 0.9354 | 0.4328 | 0.9354 | 0.9671 |
| No log | 0.9877 | 80 | 0.9693 | 0.4291 | 0.9693 | 0.9846 |
| No log | 1.0123 | 82 | 1.2601 | 0.3101 | 1.2601 | 1.1225 |
| No log | 1.0370 | 84 | 1.3541 | 0.3159 | 1.3541 | 1.1637 |
| No log | 1.0617 | 86 | 1.0227 | 0.4172 | 1.0227 | 1.0113 |
| No log | 1.0864 | 88 | 0.8540 | 0.4676 | 0.8540 | 0.9241 |
| No log | 1.1111 | 90 | 0.8910 | 0.4242 | 0.8910 | 0.9439 |
| No log | 1.1358 | 92 | 0.8407 | 0.4337 | 0.8407 | 0.9169 |
| No log | 1.1605 | 94 | 0.7857 | 0.4922 | 0.7857 | 0.8864 |
| No log | 1.1852 | 96 | 0.7804 | 0.5103 | 0.7804 | 0.8834 |
| No log | 1.2099 | 98 | 0.8342 | 0.4932 | 0.8342 | 0.9134 |
| No log | 1.2346 | 100 | 1.1123 | 0.4550 | 1.1123 | 1.0546 |
| No log | 1.2593 | 102 | 1.1468 | 0.4444 | 1.1468 | 1.0709 |
| No log | 1.2840 | 104 | 0.9609 | 0.4873 | 0.9609 | 0.9802 |
| No log | 1.3086 | 106 | 0.8539 | 0.4911 | 0.8539 | 0.9241 |
| No log | 1.3333 | 108 | 0.7671 | 0.4962 | 0.7671 | 0.8759 |
| No log | 1.3580 | 110 | 0.7492 | 0.5386 | 0.7492 | 0.8656 |
| No log | 1.3827 | 112 | 0.7373 | 0.5498 | 0.7373 | 0.8587 |
| No log | 1.4074 | 114 | 0.7877 | 0.4709 | 0.7877 | 0.8875 |
| No log | 1.4321 | 116 | 0.8004 | 0.4371 | 0.8004 | 0.8946 |
| No log | 1.4568 | 118 | 0.7340 | 0.5357 | 0.7340 | 0.8567 |
| No log | 1.4815 | 120 | 0.8117 | 0.4329 | 0.8117 | 0.9009 |
| No log | 1.5062 | 122 | 0.9365 | 0.4396 | 0.9365 | 0.9677 |
| No log | 1.5309 | 124 | 0.8106 | 0.4361 | 0.8106 | 0.9004 |
| No log | 1.5556 | 126 | 0.7603 | 0.4563 | 0.7603 | 0.8719 |
| No log | 1.5802 | 128 | 0.7343 | 0.5261 | 0.7343 | 0.8569 |
| No log | 1.6049 | 130 | 0.6843 | 0.5093 | 0.6843 | 0.8272 |
| No log | 1.6296 | 132 | 0.8238 | 0.4809 | 0.8238 | 0.9077 |
| No log | 1.6543 | 134 | 0.7660 | 0.4949 | 0.7660 | 0.8752 |
| No log | 1.6790 | 136 | 0.6498 | 0.5650 | 0.6498 | 0.8061 |
| No log | 1.7037 | 138 | 0.6412 | 0.5536 | 0.6412 | 0.8007 |
| No log | 1.7284 | 140 | 0.6419 | 0.5153 | 0.6419 | 0.8012 |
| No log | 1.7531 | 142 | 0.6821 | 0.4873 | 0.6821 | 0.8259 |
| No log | 1.7778 | 144 | 0.7142 | 0.4869 | 0.7142 | 0.8451 |
| No log | 1.8025 | 146 | 0.7211 | 0.5025 | 0.7211 | 0.8492 |
| No log | 1.8272 | 148 | 0.7051 | 0.5301 | 0.7051 | 0.8397 |
| No log | 1.8519 | 150 | 0.6504 | 0.5375 | 0.6504 | 0.8065 |
| No log | 1.8765 | 152 | 0.6246 | 0.6087 | 0.6246 | 0.7903 |
| No log | 1.9012 | 154 | 0.6056 | 0.6065 | 0.6056 | 0.7782 |
| No log | 1.9259 | 156 | 0.6219 | 0.5994 | 0.6219 | 0.7886 |
| No log | 1.9506 | 158 | 0.6534 | 0.5909 | 0.6534 | 0.8084 |
| No log | 1.9753 | 160 | 0.7703 | 0.5463 | 0.7703 | 0.8777 |
| No log | 2.0 | 162 | 0.8539 | 0.4885 | 0.8539 | 0.9241 |
| No log | 2.0247 | 164 | 0.7980 | 0.5279 | 0.7980 | 0.8933 |
| No log | 2.0494 | 166 | 0.7383 | 0.4485 | 0.7383 | 0.8593 |
| No log | 2.0741 | 168 | 0.7264 | 0.4659 | 0.7264 | 0.8523 |
| No log | 2.0988 | 170 | 0.7739 | 0.4433 | 0.7739 | 0.8797 |
| No log | 2.1235 | 172 | 0.7358 | 0.4277 | 0.7358 | 0.8578 |
| No log | 2.1481 | 174 | 0.7474 | 0.5218 | 0.7474 | 0.8645 |
| No log | 2.1728 | 176 | 0.9354 | 0.4449 | 0.9354 | 0.9672 |
| No log | 2.1975 | 178 | 0.9502 | 0.3521 | 0.9502 | 0.9748 |
| No log | 2.2222 | 180 | 0.8011 | 0.5051 | 0.8011 | 0.8951 |
| No log | 2.2469 | 182 | 0.6794 | 0.5003 | 0.6794 | 0.8243 |
| No log | 2.2716 | 184 | 0.6619 | 0.4642 | 0.6619 | 0.8136 |
| No log | 2.2963 | 186 | 0.6634 | 0.4867 | 0.6634 | 0.8145 |
| No log | 2.3210 | 188 | 0.7353 | 0.6168 | 0.7353 | 0.8575 |
| No log | 2.3457 | 190 | 0.9040 | 0.5 | 0.9040 | 0.9508 |
| No log | 2.3704 | 192 | 1.0027 | 0.4969 | 1.0027 | 1.0014 |
| No log | 2.3951 | 194 | 0.8957 | 0.4016 | 0.8957 | 0.9464 |
| No log | 2.4198 | 196 | 0.8497 | 0.4806 | 0.8497 | 0.9218 |
| No log | 2.4444 | 198 | 0.8344 | 0.4575 | 0.8344 | 0.9135 |
| No log | 2.4691 | 200 | 0.8927 | 0.4667 | 0.8927 | 0.9448 |
| No log | 2.4938 | 202 | 0.8174 | 0.5014 | 0.8174 | 0.9041 |
| No log | 2.5185 | 204 | 0.7070 | 0.5501 | 0.7070 | 0.8408 |
| No log | 2.5432 | 206 | 0.6677 | 0.5640 | 0.6677 | 0.8171 |
| No log | 2.5679 | 208 | 0.6771 | 0.4962 | 0.6771 | 0.8228 |
| No log | 2.5926 | 210 | 0.6607 | 0.5190 | 0.6607 | 0.8129 |
| No log | 2.6173 | 212 | 0.6516 | 0.6187 | 0.6516 | 0.8072 |
| No log | 2.6420 | 214 | 0.6722 | 0.6032 | 0.6722 | 0.8199 |
| No log | 2.6667 | 216 | 0.6559 | 0.6365 | 0.6559 | 0.8099 |
| No log | 2.6914 | 218 | 0.6461 | 0.6407 | 0.6461 | 0.8038 |
| No log | 2.7160 | 220 | 0.6437 | 0.6325 | 0.6437 | 0.8023 |
| No log | 2.7407 | 222 | 0.6337 | 0.5798 | 0.6337 | 0.7961 |
| No log | 2.7654 | 224 | 0.6323 | 0.6343 | 0.6323 | 0.7952 |
| No log | 2.7901 | 226 | 0.6955 | 0.5581 | 0.6955 | 0.8340 |
| No log | 2.8148 | 228 | 0.6849 | 0.5555 | 0.6849 | 0.8276 |
| No log | 2.8395 | 230 | 0.6536 | 0.5700 | 0.6536 | 0.8084 |
| No log | 2.8642 | 232 | 0.6995 | 0.5810 | 0.6995 | 0.8364 |
| No log | 2.8889 | 234 | 0.7633 | 0.5422 | 0.7633 | 0.8737 |
| No log | 2.9136 | 236 | 0.7529 | 0.6068 | 0.7529 | 0.8677 |
| No log | 2.9383 | 238 | 0.7563 | 0.6354 | 0.7563 | 0.8696 |
| No log | 2.9630 | 240 | 0.7112 | 0.6354 | 0.7112 | 0.8433 |
| No log | 2.9877 | 242 | 0.6788 | 0.6386 | 0.6788 | 0.8239 |
| No log | 3.0123 | 244 | 0.6231 | 0.6275 | 0.6231 | 0.7894 |
| No log | 3.0370 | 246 | 0.7236 | 0.6823 | 0.7236 | 0.8506 |
| No log | 3.0617 | 248 | 0.8468 | 0.5633 | 0.8468 | 0.9202 |
| No log | 3.0864 | 250 | 0.7322 | 0.5618 | 0.7322 | 0.8557 |
| No log | 3.1111 | 252 | 0.6054 | 0.5746 | 0.6054 | 0.7781 |
| No log | 3.1358 | 254 | 0.6281 | 0.4853 | 0.6281 | 0.7925 |
| No log | 3.1605 | 256 | 0.6622 | 0.4853 | 0.6622 | 0.8138 |
| No log | 3.1852 | 258 | 0.6153 | 0.6343 | 0.6153 | 0.7844 |
| No log | 3.2099 | 260 | 0.6456 | 0.6101 | 0.6456 | 0.8035 |
| No log | 3.2346 | 262 | 0.8644 | 0.5403 | 0.8644 | 0.9297 |
| No log | 3.2593 | 264 | 0.8918 | 0.5295 | 0.8918 | 0.9443 |
| No log | 3.2840 | 266 | 0.7463 | 0.5916 | 0.7463 | 0.8639 |
| No log | 3.3086 | 268 | 0.6528 | 0.6102 | 0.6528 | 0.8080 |
| No log | 3.3333 | 270 | 0.6653 | 0.5069 | 0.6653 | 0.8157 |
| No log | 3.3580 | 272 | 0.6818 | 0.5653 | 0.6818 | 0.8257 |
| No log | 3.3827 | 274 | 0.6413 | 0.5635 | 0.6413 | 0.8008 |
| No log | 3.4074 | 276 | 0.6342 | 0.5688 | 0.6342 | 0.7963 |
| No log | 3.4321 | 278 | 0.6281 | 0.6252 | 0.6281 | 0.7925 |
| No log | 3.4568 | 280 | 0.6200 | 0.5820 | 0.6200 | 0.7874 |
| No log | 3.4815 | 282 | 0.6155 | 0.6262 | 0.6155 | 0.7845 |
| No log | 3.5062 | 284 | 0.6392 | 0.5798 | 0.6392 | 0.7995 |
| No log | 3.5309 | 286 | 0.6438 | 0.5798 | 0.6438 | 0.8024 |
| No log | 3.5556 | 288 | 0.6166 | 0.6370 | 0.6166 | 0.7853 |
| No log | 3.5802 | 290 | 0.6349 | 0.5071 | 0.6349 | 0.7968 |
| No log | 3.6049 | 292 | 0.6288 | 0.5071 | 0.6288 | 0.7930 |
| No log | 3.6296 | 294 | 0.6118 | 0.5635 | 0.6118 | 0.7822 |
| No log | 3.6543 | 296 | 0.6062 | 0.6557 | 0.6062 | 0.7786 |
| No log | 3.6790 | 298 | 0.6143 | 0.6014 | 0.6143 | 0.7838 |
| No log | 3.7037 | 300 | 0.6286 | 0.5734 | 0.6286 | 0.7929 |
| No log | 3.7284 | 302 | 0.6235 | 0.5288 | 0.6235 | 0.7896 |
| No log | 3.7531 | 304 | 0.6648 | 0.4857 | 0.6648 | 0.8154 |
| No log | 3.7778 | 306 | 0.7058 | 0.4883 | 0.7058 | 0.8401 |
| No log | 3.8025 | 308 | 0.6491 | 0.4983 | 0.6491 | 0.8057 |
| No log | 3.8272 | 310 | 0.6000 | 0.6528 | 0.6000 | 0.7746 |
| No log | 3.8519 | 312 | 0.6040 | 0.6528 | 0.6040 | 0.7772 |
| No log | 3.8765 | 314 | 0.6305 | 0.6400 | 0.6305 | 0.7940 |
| No log | 3.9012 | 316 | 0.8071 | 0.5367 | 0.8071 | 0.8984 |
| No log | 3.9259 | 318 | 0.8690 | 0.5556 | 0.8690 | 0.9322 |
| No log | 3.9506 | 320 | 0.7014 | 0.4898 | 0.7014 | 0.8375 |
| No log | 3.9753 | 322 | 0.6282 | 0.6400 | 0.6282 | 0.7926 |
| No log | 4.0 | 324 | 0.6177 | 0.6400 | 0.6177 | 0.7859 |
| No log | 4.0247 | 326 | 0.6432 | 0.5748 | 0.6432 | 0.8020 |
| No log | 4.0494 | 328 | 0.7240 | 0.5151 | 0.7240 | 0.8509 |
| No log | 4.0741 | 330 | 0.7356 | 0.5151 | 0.7356 | 0.8577 |
| No log | 4.0988 | 332 | 0.6738 | 0.5566 | 0.6738 | 0.8208 |
| No log | 4.1235 | 334 | 0.6288 | 0.6374 | 0.6288 | 0.7930 |
| No log | 4.1481 | 336 | 0.6330 | 0.5797 | 0.6330 | 0.7956 |
| No log | 4.1728 | 338 | 0.6359 | 0.5943 | 0.6359 | 0.7974 |
| No log | 4.1975 | 340 | 0.6540 | 0.5421 | 0.6540 | 0.8087 |
| No log | 4.2222 | 342 | 0.7253 | 0.5350 | 0.7253 | 0.8517 |
| No log | 4.2469 | 344 | 0.7798 | 0.5670 | 0.7798 | 0.8830 |
| No log | 4.2716 | 346 | 0.7266 | 0.6035 | 0.7266 | 0.8524 |
| No log | 4.2963 | 348 | 0.6801 | 0.5638 | 0.6801 | 0.8247 |
| No log | 4.3210 | 350 | 0.6943 | 0.5505 | 0.6943 | 0.8333 |
| No log | 4.3457 | 352 | 0.7326 | 0.5530 | 0.7326 | 0.8559 |
| No log | 4.3704 | 354 | 0.7758 | 0.4983 | 0.7758 | 0.8808 |
| No log | 4.3951 | 356 | 0.7953 | 0.4983 | 0.7953 | 0.8918 |
| No log | 4.4198 | 358 | 0.7947 | 0.4983 | 0.7947 | 0.8914 |
| No log | 4.4444 | 360 | 0.7451 | 0.4983 | 0.7451 | 0.8632 |
| No log | 4.4691 | 362 | 0.6888 | 0.5314 | 0.6888 | 0.8299 |
| No log | 4.4938 | 364 | 0.6227 | 0.6175 | 0.6227 | 0.7891 |
| No log | 4.5185 | 366 | 0.5944 | 0.6380 | 0.5944 | 0.7710 |
| No log | 4.5432 | 368 | 0.5834 | 0.6597 | 0.5834 | 0.7638 |
| No log | 4.5679 | 370 | 0.6262 | 0.6386 | 0.6262 | 0.7913 |
| No log | 4.5926 | 372 | 0.7223 | 0.5824 | 0.7223 | 0.8499 |
| No log | 4.6173 | 374 | 0.7322 | 0.5824 | 0.7322 | 0.8557 |
| No log | 4.6420 | 376 | 0.6494 | 0.6112 | 0.6494 | 0.8059 |
| No log | 4.6667 | 378 | 0.6147 | 0.6387 | 0.6147 | 0.7840 |
| No log | 4.6914 | 380 | 0.5986 | 0.6175 | 0.5986 | 0.7737 |
| No log | 4.7160 | 382 | 0.6039 | 0.6054 | 0.6039 | 0.7771 |
| No log | 4.7407 | 384 | 0.6136 | 0.6219 | 0.6136 | 0.7833 |
| No log | 4.7654 | 386 | 0.6158 | 0.6528 | 0.6158 | 0.7847 |
| No log | 4.7901 | 388 | 0.6184 | 0.6470 | 0.6184 | 0.7864 |
| No log | 4.8148 | 390 | 0.6337 | 0.6039 | 0.6337 | 0.7960 |
| No log | 4.8395 | 392 | 0.6273 | 0.5845 | 0.6273 | 0.7920 |
| No log | 4.8642 | 394 | 0.6223 | 0.5746 | 0.6223 | 0.7889 |
| No log | 4.8889 | 396 | 0.6404 | 0.5710 | 0.6404 | 0.8003 |
| No log | 4.9136 | 398 | 0.6207 | 0.6198 | 0.6207 | 0.7879 |
| No log | 4.9383 | 400 | 0.6021 | 0.5859 | 0.6021 | 0.7760 |
| No log | 4.9630 | 402 | 0.6023 | 0.5859 | 0.6023 | 0.7761 |
| No log | 4.9877 | 404 | 0.6201 | 0.5722 | 0.6201 | 0.7875 |
| No log | 5.0123 | 406 | 0.6393 | 0.5361 | 0.6393 | 0.7995 |
| No log | 5.0370 | 408 | 0.6353 | 0.5361 | 0.6353 | 0.7971 |
| No log | 5.0617 | 410 | 0.6180 | 0.5391 | 0.6180 | 0.7862 |
| No log | 5.0864 | 412 | 0.6145 | 0.5274 | 0.6145 | 0.7839 |
| No log | 5.1111 | 414 | 0.6348 | 0.5183 | 0.6348 | 0.7968 |
| No log | 5.1358 | 416 | 0.6270 | 0.5288 | 0.6270 | 0.7918 |
| No log | 5.1605 | 418 | 0.6229 | 0.5288 | 0.6229 | 0.7892 |
| No log | 5.1852 | 420 | 0.6160 | 0.5485 | 0.6160 | 0.7849 |
| No log | 5.2099 | 422 | 0.6097 | 0.5610 | 0.6097 | 0.7808 |
| No log | 5.2346 | 424 | 0.6261 | 0.5868 | 0.6261 | 0.7913 |
| No log | 5.2593 | 426 | 0.6287 | 0.5419 | 0.6287 | 0.7929 |
| No log | 5.2840 | 428 | 0.6299 | 0.5274 | 0.6299 | 0.7936 |
| No log | 5.3086 | 430 | 0.6648 | 0.5246 | 0.6648 | 0.8154 |
| No log | 5.3333 | 432 | 0.7412 | 0.5799 | 0.7412 | 0.8609 |
| No log | 5.3580 | 434 | 0.7607 | 0.5292 | 0.7607 | 0.8722 |
| No log | 5.3827 | 436 | 0.6835 | 0.5992 | 0.6835 | 0.8267 |
| No log | 5.4074 | 438 | 0.6408 | 0.5565 | 0.6408 | 0.8005 |
| No log | 5.4321 | 440 | 0.6184 | 0.5710 | 0.6184 | 0.7864 |
| No log | 5.4568 | 442 | 0.6096 | 0.5565 | 0.6096 | 0.7807 |
| No log | 5.4815 | 444 | 0.6277 | 0.5751 | 0.6277 | 0.7923 |
| No log | 5.5062 | 446 | 0.6491 | 0.6188 | 0.6491 | 0.8057 |
| No log | 5.5309 | 448 | 0.6442 | 0.5992 | 0.6442 | 0.8026 |
| No log | 5.5556 | 450 | 0.6285 | 0.6021 | 0.6285 | 0.7928 |
| No log | 5.5802 | 452 | 0.6262 | 0.6051 | 0.6262 | 0.7913 |
| No log | 5.6049 | 454 | 0.6079 | 0.5698 | 0.6079 | 0.7797 |
| No log | 5.6296 | 456 | 0.5702 | 0.5859 | 0.5702 | 0.7551 |
| No log | 5.6543 | 458 | 0.6221 | 0.6232 | 0.6221 | 0.7887 |
| No log | 5.6790 | 460 | 0.6863 | 0.6032 | 0.6863 | 0.8284 |
| No log | 5.7037 | 462 | 0.6555 | 0.6221 | 0.6555 | 0.8096 |
| No log | 5.7284 | 464 | 0.5954 | 0.5647 | 0.5954 | 0.7716 |
| No log | 5.7531 | 466 | 0.5945 | 0.5932 | 0.5945 | 0.7710 |
| No log | 5.7778 | 468 | 0.5898 | 0.5833 | 0.5898 | 0.7680 |
| No log | 5.8025 | 470 | 0.6259 | 0.6126 | 0.6259 | 0.7911 |
| No log | 5.8272 | 472 | 0.6610 | 0.6074 | 0.6610 | 0.8130 |
| No log | 5.8519 | 474 | 0.6501 | 0.6091 | 0.6501 | 0.8063 |
| No log | 5.8765 | 476 | 0.6128 | 0.6435 | 0.6128 | 0.7828 |
| No log | 5.9012 | 478 | 0.6111 | 0.6602 | 0.6111 | 0.7817 |
| No log | 5.9259 | 480 | 0.6064 | 0.6641 | 0.6064 | 0.7787 |
| No log | 5.9506 | 482 | 0.5978 | 0.6054 | 0.5978 | 0.7732 |
| No log | 5.9753 | 484 | 0.5932 | 0.5522 | 0.5932 | 0.7702 |
| No log | 6.0 | 486 | 0.6134 | 0.5331 | 0.6134 | 0.7832 |
| No log | 6.0247 | 488 | 0.6584 | 0.5244 | 0.6584 | 0.8114 |
| No log | 6.0494 | 490 | 0.6651 | 0.5690 | 0.6651 | 0.8155 |
| No log | 6.0741 | 492 | 0.6053 | 0.6244 | 0.6053 | 0.7780 |
| No log | 6.0988 | 494 | 0.5541 | 0.5644 | 0.5541 | 0.7444 |
| No log | 6.1235 | 496 | 0.5798 | 0.6305 | 0.5798 | 0.7614 |
| No log | 6.1481 | 498 | 0.6173 | 0.6413 | 0.6173 | 0.7857 |
| 0.357 | 6.1728 | 500 | 0.6214 | 0.6221 | 0.6214 | 0.7883 |
| 0.357 | 6.1975 | 502 | 0.5948 | 0.5698 | 0.5948 | 0.7712 |
| 0.357 | 6.2222 | 504 | 0.5742 | 0.5823 | 0.5742 | 0.7577 |
| 0.357 | 6.2469 | 506 | 0.5723 | 0.6241 | 0.5723 | 0.7565 |
| 0.357 | 6.2716 | 508 | 0.5606 | 0.6025 | 0.5606 | 0.7487 |
| 0.357 | 6.2963 | 510 | 0.5585 | 0.6025 | 0.5585 | 0.7473 |
| 0.357 | 6.3210 | 512 | 0.5991 | 0.6082 | 0.5991 | 0.7740 |
| 0.357 | 6.3457 | 514 | 0.7159 | 0.6584 | 0.7159 | 0.8461 |
| 0.357 | 6.3704 | 516 | 0.8504 | 0.5686 | 0.8504 | 0.9221 |
| 0.357 | 6.3951 | 518 | 0.8362 | 0.5686 | 0.8362 | 0.9144 |
| 0.357 | 6.4198 | 520 | 0.7274 | 0.6377 | 0.7274 | 0.8529 |
| 0.357 | 6.4444 | 522 | 0.6026 | 0.6082 | 0.6026 | 0.7763 |
| 0.357 | 6.4691 | 524 | 0.5771 | 0.6102 | 0.5771 | 0.7597 |
| 0.357 | 6.4938 | 526 | 0.5970 | 0.6073 | 0.5970 | 0.7727 |
| 0.357 | 6.5185 | 528 | 0.6290 | 0.6063 | 0.6290 | 0.7931 |
| 0.357 | 6.5432 | 530 | 0.6342 | 0.6063 | 0.6342 | 0.7963 |
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_k16_task5_organization
Base model
aubmindlab/bert-base-arabertv02