Instructions to use MayBashendy/ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k11_task5_organization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k11_task5_organization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k11_task5_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k11_task5_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k11_task5_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k11_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: 0.8017
- Qwk: 0.6898
- Mse: 0.8017
- Rmse: 0.8954
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 | 0.0488 | 2 | 2.4405 | 0.0285 | 2.4405 | 1.5622 |
| No log | 0.0976 | 4 | 1.6229 | 0.1548 | 1.6229 | 1.2739 |
| No log | 0.1463 | 6 | 1.5256 | 0.0987 | 1.5256 | 1.2351 |
| No log | 0.1951 | 8 | 1.5798 | 0.1766 | 1.5798 | 1.2569 |
| No log | 0.2439 | 10 | 1.4788 | 0.2350 | 1.4788 | 1.2161 |
| No log | 0.2927 | 12 | 1.6493 | 0.2655 | 1.6493 | 1.2842 |
| No log | 0.3415 | 14 | 1.6411 | 0.2848 | 1.6411 | 1.2811 |
| No log | 0.3902 | 16 | 1.4069 | 0.3448 | 1.4069 | 1.1861 |
| No log | 0.4390 | 18 | 1.1949 | 0.3287 | 1.1949 | 1.0931 |
| No log | 0.4878 | 20 | 1.1040 | 0.3787 | 1.1040 | 1.0507 |
| No log | 0.5366 | 22 | 1.0803 | 0.4117 | 1.0803 | 1.0394 |
| No log | 0.5854 | 24 | 1.0959 | 0.4181 | 1.0959 | 1.0469 |
| No log | 0.6341 | 26 | 1.1550 | 0.4580 | 1.1550 | 1.0747 |
| No log | 0.6829 | 28 | 1.1167 | 0.4997 | 1.1167 | 1.0567 |
| No log | 0.7317 | 30 | 1.0591 | 0.3972 | 1.0591 | 1.0291 |
| No log | 0.7805 | 32 | 0.9993 | 0.3985 | 0.9993 | 0.9996 |
| No log | 0.8293 | 34 | 0.9738 | 0.4625 | 0.9738 | 0.9868 |
| No log | 0.8780 | 36 | 0.9766 | 0.5263 | 0.9766 | 0.9882 |
| No log | 0.9268 | 38 | 1.0143 | 0.5651 | 1.0143 | 1.0071 |
| No log | 0.9756 | 40 | 0.9883 | 0.5141 | 0.9883 | 0.9941 |
| No log | 1.0244 | 42 | 1.0640 | 0.4783 | 1.0640 | 1.0315 |
| No log | 1.0732 | 44 | 1.1611 | 0.4841 | 1.1611 | 1.0776 |
| No log | 1.1220 | 46 | 1.2152 | 0.4901 | 1.2152 | 1.1024 |
| No log | 1.1707 | 48 | 1.1195 | 0.4757 | 1.1195 | 1.0581 |
| No log | 1.2195 | 50 | 1.0044 | 0.5041 | 1.0044 | 1.0022 |
| No log | 1.2683 | 52 | 0.9794 | 0.5318 | 0.9794 | 0.9896 |
| No log | 1.3171 | 54 | 0.9635 | 0.5951 | 0.9635 | 0.9816 |
| No log | 1.3659 | 56 | 0.9396 | 0.6192 | 0.9396 | 0.9693 |
| No log | 1.4146 | 58 | 0.9067 | 0.5883 | 0.9067 | 0.9522 |
| No log | 1.4634 | 60 | 0.9333 | 0.5486 | 0.9333 | 0.9661 |
| No log | 1.5122 | 62 | 1.0469 | 0.5360 | 1.0469 | 1.0232 |
| No log | 1.5610 | 64 | 1.0963 | 0.5551 | 1.0963 | 1.0471 |
| No log | 1.6098 | 66 | 1.1156 | 0.5664 | 1.1156 | 1.0562 |
| No log | 1.6585 | 68 | 1.0541 | 0.5316 | 1.0541 | 1.0267 |
| No log | 1.7073 | 70 | 1.0114 | 0.5123 | 1.0114 | 1.0057 |
| No log | 1.7561 | 72 | 1.0125 | 0.4867 | 1.0125 | 1.0062 |
| No log | 1.8049 | 74 | 1.0681 | 0.5134 | 1.0681 | 1.0335 |
| No log | 1.8537 | 76 | 1.1793 | 0.5399 | 1.1793 | 1.0860 |
| No log | 1.9024 | 78 | 1.1860 | 0.5318 | 1.1860 | 1.0891 |
| No log | 1.9512 | 80 | 1.0115 | 0.6056 | 1.0115 | 1.0058 |
| No log | 2.0 | 82 | 0.8683 | 0.5682 | 0.8683 | 0.9318 |
| No log | 2.0488 | 84 | 0.8137 | 0.6243 | 0.8137 | 0.9020 |
| No log | 2.0976 | 86 | 0.7924 | 0.6284 | 0.7924 | 0.8902 |
| No log | 2.1463 | 88 | 0.8094 | 0.6376 | 0.8094 | 0.8996 |
| No log | 2.1951 | 90 | 0.9142 | 0.6678 | 0.9142 | 0.9561 |
| No log | 2.2439 | 92 | 1.0692 | 0.6424 | 1.0692 | 1.0340 |
| No log | 2.2927 | 94 | 1.0409 | 0.6513 | 1.0409 | 1.0202 |
| No log | 2.3415 | 96 | 1.0123 | 0.6432 | 1.0123 | 1.0061 |
| No log | 2.3902 | 98 | 0.9733 | 0.6143 | 0.9733 | 0.9866 |
| No log | 2.4390 | 100 | 0.9434 | 0.6043 | 0.9434 | 0.9713 |
| No log | 2.4878 | 102 | 0.9042 | 0.6191 | 0.9042 | 0.9509 |
| No log | 2.5366 | 104 | 0.8993 | 0.5798 | 0.8993 | 0.9483 |
| No log | 2.5854 | 106 | 0.8813 | 0.5739 | 0.8813 | 0.9388 |
| No log | 2.6341 | 108 | 0.8072 | 0.6400 | 0.8072 | 0.8984 |
| No log | 2.6829 | 110 | 0.8376 | 0.6234 | 0.8376 | 0.9152 |
| No log | 2.7317 | 112 | 1.0638 | 0.6501 | 1.0638 | 1.0314 |
| No log | 2.7805 | 114 | 1.1967 | 0.5977 | 1.1967 | 1.0939 |
| No log | 2.8293 | 116 | 1.0761 | 0.6566 | 1.0761 | 1.0374 |
| No log | 2.8780 | 118 | 0.8415 | 0.6972 | 0.8415 | 0.9173 |
| No log | 2.9268 | 120 | 0.6858 | 0.7291 | 0.6858 | 0.8281 |
| No log | 2.9756 | 122 | 0.6601 | 0.7290 | 0.6601 | 0.8125 |
| No log | 3.0244 | 124 | 0.8000 | 0.7292 | 0.8000 | 0.8944 |
| No log | 3.0732 | 126 | 1.0615 | 0.6495 | 1.0615 | 1.0303 |
| No log | 3.1220 | 128 | 1.0856 | 0.6428 | 1.0856 | 1.0419 |
| No log | 3.1707 | 130 | 0.9763 | 0.6598 | 0.9763 | 0.9881 |
| No log | 3.2195 | 132 | 0.8531 | 0.7060 | 0.8531 | 0.9236 |
| No log | 3.2683 | 134 | 0.8712 | 0.7147 | 0.8712 | 0.9334 |
| No log | 3.3171 | 136 | 0.9950 | 0.6874 | 0.9950 | 0.9975 |
| No log | 3.3659 | 138 | 1.1842 | 0.6767 | 1.1842 | 1.0882 |
| No log | 3.4146 | 140 | 1.1983 | 0.6819 | 1.1983 | 1.0947 |
| No log | 3.4634 | 142 | 0.9763 | 0.6847 | 0.9763 | 0.9881 |
| No log | 3.5122 | 144 | 0.8502 | 0.6823 | 0.8502 | 0.9220 |
| No log | 3.5610 | 146 | 0.8546 | 0.6838 | 0.8546 | 0.9244 |
| No log | 3.6098 | 148 | 0.9020 | 0.6657 | 0.9020 | 0.9497 |
| No log | 3.6585 | 150 | 1.0714 | 0.6082 | 1.0714 | 1.0351 |
| No log | 3.7073 | 152 | 1.0448 | 0.6284 | 1.0448 | 1.0221 |
| No log | 3.7561 | 154 | 0.8997 | 0.6520 | 0.8997 | 0.9485 |
| No log | 3.8049 | 156 | 0.8063 | 0.7160 | 0.8063 | 0.8979 |
| No log | 3.8537 | 158 | 0.7162 | 0.6877 | 0.7162 | 0.8463 |
| No log | 3.9024 | 160 | 0.7204 | 0.7127 | 0.7204 | 0.8488 |
| No log | 3.9512 | 162 | 0.7571 | 0.7147 | 0.7571 | 0.8701 |
| No log | 4.0 | 164 | 0.8436 | 0.6762 | 0.8436 | 0.9185 |
| No log | 4.0488 | 166 | 0.8893 | 0.6554 | 0.8893 | 0.9430 |
| No log | 4.0976 | 168 | 0.9858 | 0.6381 | 0.9858 | 0.9929 |
| No log | 4.1463 | 170 | 1.0483 | 0.6347 | 1.0483 | 1.0239 |
| No log | 4.1951 | 172 | 0.9309 | 0.6473 | 0.9309 | 0.9648 |
| No log | 4.2439 | 174 | 0.7771 | 0.6900 | 0.7771 | 0.8815 |
| No log | 4.2927 | 176 | 0.7464 | 0.6897 | 0.7464 | 0.8639 |
| No log | 4.3415 | 178 | 0.7209 | 0.7083 | 0.7209 | 0.8491 |
| No log | 4.3902 | 180 | 0.7413 | 0.7085 | 0.7413 | 0.8610 |
| No log | 4.4390 | 182 | 0.8758 | 0.6604 | 0.8758 | 0.9358 |
| No log | 4.4878 | 184 | 0.9545 | 0.6553 | 0.9545 | 0.9770 |
| No log | 4.5366 | 186 | 0.8507 | 0.6855 | 0.8507 | 0.9224 |
| No log | 4.5854 | 188 | 0.7881 | 0.7012 | 0.7881 | 0.8877 |
| No log | 4.6341 | 190 | 0.7830 | 0.6957 | 0.7830 | 0.8849 |
| No log | 4.6829 | 192 | 0.8567 | 0.7037 | 0.8567 | 0.9256 |
| No log | 4.7317 | 194 | 0.9097 | 0.7040 | 0.9097 | 0.9538 |
| No log | 4.7805 | 196 | 0.8319 | 0.7123 | 0.8319 | 0.9121 |
| No log | 4.8293 | 198 | 0.7354 | 0.7499 | 0.7354 | 0.8576 |
| No log | 4.8780 | 200 | 0.7385 | 0.7496 | 0.7385 | 0.8594 |
| No log | 4.9268 | 202 | 0.8070 | 0.7359 | 0.8070 | 0.8984 |
| No log | 4.9756 | 204 | 0.8430 | 0.7173 | 0.8430 | 0.9182 |
| No log | 5.0244 | 206 | 0.9564 | 0.6793 | 0.9564 | 0.9780 |
| No log | 5.0732 | 208 | 1.0679 | 0.6264 | 1.0679 | 1.0334 |
| No log | 5.1220 | 210 | 1.0744 | 0.6239 | 1.0744 | 1.0365 |
| No log | 5.1707 | 212 | 0.9642 | 0.6817 | 0.9642 | 0.9819 |
| No log | 5.2195 | 214 | 0.9023 | 0.6884 | 0.9023 | 0.9499 |
| No log | 5.2683 | 216 | 0.8363 | 0.6979 | 0.8363 | 0.9145 |
| No log | 5.3171 | 218 | 0.8114 | 0.6979 | 0.8114 | 0.9008 |
| No log | 5.3659 | 220 | 0.7950 | 0.6989 | 0.7950 | 0.8916 |
| No log | 5.4146 | 222 | 0.7866 | 0.6797 | 0.7866 | 0.8869 |
| No log | 5.4634 | 224 | 0.7367 | 0.6979 | 0.7367 | 0.8583 |
| No log | 5.5122 | 226 | 0.7457 | 0.6944 | 0.7457 | 0.8636 |
| No log | 5.5610 | 228 | 0.8096 | 0.6712 | 0.8096 | 0.8998 |
| No log | 5.6098 | 230 | 0.9338 | 0.6460 | 0.9338 | 0.9663 |
| No log | 5.6585 | 232 | 1.1643 | 0.6178 | 1.1643 | 1.0790 |
| No log | 5.7073 | 234 | 1.3837 | 0.6008 | 1.3837 | 1.1763 |
| No log | 5.7561 | 236 | 1.3902 | 0.6008 | 1.3902 | 1.1790 |
| No log | 5.8049 | 238 | 1.2329 | 0.6232 | 1.2329 | 1.1104 |
| No log | 5.8537 | 240 | 1.0534 | 0.6364 | 1.0534 | 1.0263 |
| No log | 5.9024 | 242 | 0.8775 | 0.6720 | 0.8775 | 0.9368 |
| No log | 5.9512 | 244 | 0.8198 | 0.6600 | 0.8198 | 0.9055 |
| No log | 6.0 | 246 | 0.8106 | 0.6721 | 0.8106 | 0.9003 |
| No log | 6.0488 | 248 | 0.8556 | 0.6812 | 0.8556 | 0.9250 |
| No log | 6.0976 | 250 | 0.9316 | 0.6500 | 0.9316 | 0.9652 |
| No log | 6.1463 | 252 | 1.0218 | 0.6415 | 1.0218 | 1.0109 |
| No log | 6.1951 | 254 | 1.0075 | 0.6415 | 1.0075 | 1.0037 |
| No log | 6.2439 | 256 | 0.9557 | 0.6331 | 0.9557 | 0.9776 |
| No log | 6.2927 | 258 | 0.8442 | 0.6830 | 0.8442 | 0.9188 |
| No log | 6.3415 | 260 | 0.8197 | 0.7114 | 0.8197 | 0.9054 |
| No log | 6.3902 | 262 | 0.8910 | 0.6609 | 0.8910 | 0.9439 |
| No log | 6.4390 | 264 | 0.9408 | 0.6609 | 0.9408 | 0.9700 |
| No log | 6.4878 | 266 | 0.9412 | 0.6609 | 0.9412 | 0.9702 |
| No log | 6.5366 | 268 | 0.9222 | 0.6841 | 0.9222 | 0.9603 |
| No log | 6.5854 | 270 | 0.9526 | 0.6704 | 0.9526 | 0.9760 |
| No log | 6.6341 | 272 | 1.0019 | 0.6491 | 1.0019 | 1.0009 |
| No log | 6.6829 | 274 | 0.9952 | 0.6538 | 0.9952 | 0.9976 |
| No log | 6.7317 | 276 | 0.9799 | 0.6680 | 0.9799 | 0.9899 |
| No log | 6.7805 | 278 | 0.8870 | 0.6625 | 0.8870 | 0.9418 |
| No log | 6.8293 | 280 | 0.8050 | 0.6641 | 0.8050 | 0.8972 |
| No log | 6.8780 | 282 | 0.7534 | 0.6617 | 0.7534 | 0.8680 |
| No log | 6.9268 | 284 | 0.7573 | 0.6667 | 0.7573 | 0.8702 |
| No log | 6.9756 | 286 | 0.8019 | 0.6624 | 0.8019 | 0.8955 |
| No log | 7.0244 | 288 | 0.8071 | 0.6624 | 0.8071 | 0.8984 |
| No log | 7.0732 | 290 | 0.7806 | 0.6605 | 0.7806 | 0.8835 |
| No log | 7.1220 | 292 | 0.8014 | 0.6561 | 0.8014 | 0.8952 |
| No log | 7.1707 | 294 | 0.8675 | 0.6722 | 0.8675 | 0.9314 |
| No log | 7.2195 | 296 | 0.9354 | 0.6720 | 0.9354 | 0.9672 |
| No log | 7.2683 | 298 | 0.9901 | 0.6704 | 0.9901 | 0.9951 |
| No log | 7.3171 | 300 | 0.9775 | 0.6704 | 0.9775 | 0.9887 |
| No log | 7.3659 | 302 | 0.9420 | 0.6720 | 0.9420 | 0.9705 |
| No log | 7.4146 | 304 | 0.8898 | 0.6551 | 0.8898 | 0.9433 |
| No log | 7.4634 | 306 | 0.8090 | 0.6755 | 0.8090 | 0.8994 |
| No log | 7.5122 | 308 | 0.7761 | 0.6883 | 0.7761 | 0.8809 |
| No log | 7.5610 | 310 | 0.7538 | 0.6860 | 0.7538 | 0.8682 |
| No log | 7.6098 | 312 | 0.7369 | 0.7077 | 0.7369 | 0.8584 |
| No log | 7.6585 | 314 | 0.7379 | 0.7080 | 0.7379 | 0.8590 |
| No log | 7.7073 | 316 | 0.7707 | 0.6883 | 0.7707 | 0.8779 |
| No log | 7.7561 | 318 | 0.8225 | 0.6770 | 0.8225 | 0.9069 |
| No log | 7.8049 | 320 | 0.8493 | 0.6919 | 0.8493 | 0.9216 |
| No log | 7.8537 | 322 | 0.8794 | 0.6944 | 0.8794 | 0.9378 |
| No log | 7.9024 | 324 | 0.9032 | 0.6883 | 0.9032 | 0.9504 |
| No log | 7.9512 | 326 | 0.8897 | 0.6944 | 0.8897 | 0.9432 |
| No log | 8.0 | 328 | 0.8412 | 0.6988 | 0.8412 | 0.9171 |
| No log | 8.0488 | 330 | 0.7886 | 0.6929 | 0.7886 | 0.8881 |
| No log | 8.0976 | 332 | 0.7625 | 0.7008 | 0.7625 | 0.8732 |
| No log | 8.1463 | 334 | 0.7714 | 0.7065 | 0.7714 | 0.8783 |
| No log | 8.1951 | 336 | 0.8037 | 0.7002 | 0.8037 | 0.8965 |
| No log | 8.2439 | 338 | 0.8655 | 0.6884 | 0.8655 | 0.9303 |
| No log | 8.2927 | 340 | 0.9201 | 0.6815 | 0.9201 | 0.9592 |
| No log | 8.3415 | 342 | 0.9234 | 0.6815 | 0.9234 | 0.9610 |
| No log | 8.3902 | 344 | 0.9402 | 0.6727 | 0.9402 | 0.9696 |
| No log | 8.4390 | 346 | 0.9669 | 0.6585 | 0.9669 | 0.9833 |
| No log | 8.4878 | 348 | 0.9587 | 0.6585 | 0.9587 | 0.9791 |
| No log | 8.5366 | 350 | 0.9211 | 0.6877 | 0.9211 | 0.9597 |
| No log | 8.5854 | 352 | 0.8782 | 0.6813 | 0.8782 | 0.9371 |
| No log | 8.6341 | 354 | 0.8565 | 0.6813 | 0.8565 | 0.9255 |
| No log | 8.6829 | 356 | 0.8467 | 0.6907 | 0.8467 | 0.9201 |
| No log | 8.7317 | 358 | 0.8411 | 0.6907 | 0.8411 | 0.9171 |
| No log | 8.7805 | 360 | 0.8379 | 0.6772 | 0.8379 | 0.9154 |
| No log | 8.8293 | 362 | 0.8442 | 0.6972 | 0.8442 | 0.9188 |
| No log | 8.8780 | 364 | 0.8442 | 0.6972 | 0.8442 | 0.9188 |
| No log | 8.9268 | 366 | 0.8415 | 0.6972 | 0.8415 | 0.9173 |
| No log | 8.9756 | 368 | 0.8405 | 0.6972 | 0.8405 | 0.9168 |
| No log | 9.0244 | 370 | 0.8488 | 0.6972 | 0.8488 | 0.9213 |
| No log | 9.0732 | 372 | 0.8509 | 0.6972 | 0.8509 | 0.9225 |
| No log | 9.1220 | 374 | 0.8552 | 0.6972 | 0.8552 | 0.9248 |
| No log | 9.1707 | 376 | 0.8637 | 0.6878 | 0.8637 | 0.9293 |
| No log | 9.2195 | 378 | 0.8779 | 0.6878 | 0.8779 | 0.9370 |
| No log | 9.2683 | 380 | 0.8892 | 0.6878 | 0.8892 | 0.9430 |
| No log | 9.3171 | 382 | 0.8923 | 0.6884 | 0.8923 | 0.9446 |
| No log | 9.3659 | 384 | 0.8998 | 0.6884 | 0.8998 | 0.9486 |
| No log | 9.4146 | 386 | 0.8939 | 0.6884 | 0.8939 | 0.9455 |
| No log | 9.4634 | 388 | 0.8890 | 0.6884 | 0.8890 | 0.9428 |
| No log | 9.5122 | 390 | 0.8742 | 0.6878 | 0.8742 | 0.9350 |
| No log | 9.5610 | 392 | 0.8521 | 0.6745 | 0.8521 | 0.9231 |
| No log | 9.6098 | 394 | 0.8372 | 0.6904 | 0.8372 | 0.9150 |
| No log | 9.6585 | 396 | 0.8282 | 0.6904 | 0.8282 | 0.9100 |
| No log | 9.7073 | 398 | 0.8236 | 0.6904 | 0.8236 | 0.9075 |
| No log | 9.7561 | 400 | 0.8193 | 0.6898 | 0.8193 | 0.9051 |
| No log | 9.8049 | 402 | 0.8135 | 0.6898 | 0.8135 | 0.9019 |
| No log | 9.8537 | 404 | 0.8089 | 0.6898 | 0.8089 | 0.8994 |
| No log | 9.9024 | 406 | 0.8051 | 0.6898 | 0.8051 | 0.8973 |
| No log | 9.9512 | 408 | 0.8026 | 0.6898 | 0.8026 | 0.8959 |
| No log | 10.0 | 410 | 0.8017 | 0.6898 | 0.8017 | 0.8954 |
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_FineTuningAraBERT_run2_AugV5_k11_task5_organization
Base model
aubmindlab/bert-base-arabertv02