Instructions to use MayBashendy/ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k7_task3_organization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MayBashendy/ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k7_task3_organization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MayBashendy/ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k7_task3_organization")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MayBashendy/ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k7_task3_organization") model = AutoModelForSequenceClassification.from_pretrained("MayBashendy/ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k7_task3_organization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k7_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: 0.5457
- Qwk: 0.3371
- Mse: 0.5457
- Rmse: 0.7387
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 | 0.0465 | 2 | 3.0879 | -0.0205 | 3.0879 | 1.7573 |
| No log | 0.0930 | 4 | 1.5661 | -0.0070 | 1.5661 | 1.2514 |
| No log | 0.1395 | 6 | 1.4407 | 0.0790 | 1.4407 | 1.2003 |
| No log | 0.1860 | 8 | 1.0780 | 0.0462 | 1.0780 | 1.0383 |
| No log | 0.2326 | 10 | 0.7179 | 0.2258 | 0.7179 | 0.8473 |
| No log | 0.2791 | 12 | 1.1474 | 0.0288 | 1.1474 | 1.0712 |
| No log | 0.3256 | 14 | 1.0640 | 0.1333 | 1.0640 | 1.0315 |
| No log | 0.3721 | 16 | 1.2810 | 0.0977 | 1.2810 | 1.1318 |
| No log | 0.4186 | 18 | 1.6912 | 0.0210 | 1.6912 | 1.3005 |
| No log | 0.4651 | 20 | 1.1775 | 0.0255 | 1.1775 | 1.0851 |
| No log | 0.5116 | 22 | 0.8292 | 0.0794 | 0.8292 | 0.9106 |
| No log | 0.5581 | 24 | 0.6583 | 0.1813 | 0.6583 | 0.8113 |
| No log | 0.6047 | 26 | 0.5867 | 0.1206 | 0.5867 | 0.7660 |
| No log | 0.6512 | 28 | 0.8021 | 0.1925 | 0.8021 | 0.8956 |
| No log | 0.6977 | 30 | 1.0120 | 0.1333 | 1.0120 | 1.0060 |
| No log | 0.7442 | 32 | 0.6314 | 0.1111 | 0.6314 | 0.7946 |
| No log | 0.7907 | 34 | 0.5692 | 0.1008 | 0.5692 | 0.7544 |
| No log | 0.8372 | 36 | 0.5702 | 0.0476 | 0.5702 | 0.7551 |
| No log | 0.8837 | 38 | 0.5809 | 0.0476 | 0.5809 | 0.7622 |
| No log | 0.9302 | 40 | 0.7224 | 0.0345 | 0.7224 | 0.8499 |
| No log | 0.9767 | 42 | 0.9930 | 0.0871 | 0.9930 | 0.9965 |
| No log | 1.0233 | 44 | 0.9032 | 0.1131 | 0.9032 | 0.9504 |
| No log | 1.0698 | 46 | 0.6322 | 0.0725 | 0.6322 | 0.7951 |
| No log | 1.1163 | 48 | 0.6257 | 0.0303 | 0.6257 | 0.7910 |
| No log | 1.1628 | 50 | 0.7413 | 0.1269 | 0.7413 | 0.8610 |
| No log | 1.2093 | 52 | 0.9500 | 0.1071 | 0.9500 | 0.9747 |
| No log | 1.2558 | 54 | 0.7197 | 0.0833 | 0.7197 | 0.8483 |
| No log | 1.3023 | 56 | 0.7211 | 0.1138 | 0.7211 | 0.8492 |
| No log | 1.3488 | 58 | 0.7070 | 0.1209 | 0.7070 | 0.8408 |
| No log | 1.3953 | 60 | 0.9137 | 0.2000 | 0.9137 | 0.9559 |
| No log | 1.4419 | 62 | 1.0230 | 0.2000 | 1.0230 | 1.0114 |
| No log | 1.4884 | 64 | 0.6613 | 0.2161 | 0.6613 | 0.8132 |
| No log | 1.5349 | 66 | 0.6228 | 0.0805 | 0.6228 | 0.7892 |
| No log | 1.5814 | 68 | 0.6214 | 0.1243 | 0.6214 | 0.7883 |
| No log | 1.6279 | 70 | 0.5767 | 0.2381 | 0.5767 | 0.7594 |
| No log | 1.6744 | 72 | 0.6900 | 0.1765 | 0.6900 | 0.8306 |
| No log | 1.7209 | 74 | 0.7256 | 0.1238 | 0.7256 | 0.8518 |
| No log | 1.7674 | 76 | 0.9938 | 0.0947 | 0.9938 | 0.9969 |
| No log | 1.8140 | 78 | 0.9801 | 0.1000 | 0.9801 | 0.9900 |
| No log | 1.8605 | 80 | 0.5554 | 0.4152 | 0.5554 | 0.7452 |
| No log | 1.9070 | 82 | 0.6514 | 0.1086 | 0.6514 | 0.8071 |
| No log | 1.9535 | 84 | 0.6580 | 0.1111 | 0.6580 | 0.8112 |
| No log | 2.0 | 86 | 0.4792 | 0.2208 | 0.4792 | 0.6923 |
| No log | 2.0465 | 88 | 0.7027 | 0.2300 | 0.7027 | 0.8383 |
| No log | 2.0930 | 90 | 0.8633 | 0.1453 | 0.8633 | 0.9292 |
| No log | 2.1395 | 92 | 0.6372 | 0.3035 | 0.6372 | 0.7982 |
| No log | 2.1860 | 94 | 0.5217 | 0.3939 | 0.5217 | 0.7223 |
| No log | 2.2326 | 96 | 0.5393 | 0.3333 | 0.5393 | 0.7344 |
| No log | 2.2791 | 98 | 0.5862 | 0.2917 | 0.5862 | 0.7656 |
| No log | 2.3256 | 100 | 0.9908 | 0.1935 | 0.9908 | 0.9954 |
| No log | 2.3721 | 102 | 1.1991 | 0.1587 | 1.1991 | 1.0951 |
| No log | 2.4186 | 104 | 0.8084 | 0.2146 | 0.8084 | 0.8991 |
| No log | 2.4651 | 106 | 0.5172 | 0.3829 | 0.5172 | 0.7192 |
| No log | 2.5116 | 108 | 0.7838 | 0.2000 | 0.7838 | 0.8853 |
| No log | 2.5581 | 110 | 0.8006 | 0.2000 | 0.8006 | 0.8947 |
| No log | 2.6047 | 112 | 0.5197 | 0.4667 | 0.5197 | 0.7209 |
| No log | 2.6512 | 114 | 0.6246 | 0.2692 | 0.6246 | 0.7903 |
| No log | 2.6977 | 116 | 0.6971 | 0.1628 | 0.6971 | 0.8349 |
| No log | 2.7442 | 118 | 0.4861 | 0.5 | 0.4861 | 0.6972 |
| No log | 2.7907 | 120 | 0.6145 | 0.2941 | 0.6145 | 0.7839 |
| No log | 2.8372 | 122 | 0.6111 | 0.2941 | 0.6111 | 0.7817 |
| No log | 2.8837 | 124 | 0.5127 | 0.5132 | 0.5127 | 0.7161 |
| No log | 2.9302 | 126 | 0.5641 | 0.4783 | 0.5641 | 0.7511 |
| No log | 2.9767 | 128 | 0.5444 | 0.4764 | 0.5444 | 0.7378 |
| No log | 3.0233 | 130 | 0.5980 | 0.4286 | 0.5980 | 0.7733 |
| No log | 3.0698 | 132 | 0.6193 | 0.4336 | 0.6193 | 0.7869 |
| No log | 3.1163 | 134 | 0.7946 | 0.2320 | 0.7946 | 0.8914 |
| No log | 3.1628 | 136 | 0.8277 | 0.2129 | 0.8277 | 0.9098 |
| No log | 3.2093 | 138 | 0.6638 | 0.3303 | 0.6638 | 0.8147 |
| No log | 3.2558 | 140 | 0.5704 | 0.4229 | 0.5704 | 0.7552 |
| No log | 3.3023 | 142 | 0.5541 | 0.3663 | 0.5541 | 0.7444 |
| No log | 3.3488 | 144 | 0.6571 | 0.2941 | 0.6571 | 0.8106 |
| No log | 3.3953 | 146 | 0.8226 | 0.2510 | 0.8226 | 0.9070 |
| No log | 3.4419 | 148 | 0.6461 | 0.2965 | 0.6461 | 0.8038 |
| No log | 3.4884 | 150 | 0.5515 | 0.2626 | 0.5515 | 0.7426 |
| No log | 3.5349 | 152 | 0.5998 | 0.3913 | 0.5998 | 0.7745 |
| No log | 3.5814 | 154 | 0.5913 | 0.2889 | 0.5913 | 0.7690 |
| No log | 3.6279 | 156 | 0.6281 | 0.3271 | 0.6281 | 0.7925 |
| No log | 3.6744 | 158 | 1.0552 | 0.1672 | 1.0552 | 1.0272 |
| No log | 3.7209 | 160 | 1.0118 | 0.1944 | 1.0118 | 1.0059 |
| No log | 3.7674 | 162 | 0.6170 | 0.3271 | 0.6170 | 0.7855 |
| No log | 3.8140 | 164 | 0.5736 | 0.4051 | 0.5736 | 0.7574 |
| No log | 3.8605 | 166 | 0.5543 | 0.4051 | 0.5543 | 0.7445 |
| No log | 3.9070 | 168 | 0.7746 | 0.2459 | 0.7746 | 0.8801 |
| No log | 3.9535 | 170 | 1.0216 | 0.1661 | 1.0216 | 1.0108 |
| No log | 4.0 | 172 | 0.9988 | 0.1343 | 0.9988 | 0.9994 |
| No log | 4.0465 | 174 | 0.6617 | 0.3061 | 0.6617 | 0.8134 |
| No log | 4.0930 | 176 | 0.5891 | 0.4098 | 0.5891 | 0.7675 |
| No log | 4.1395 | 178 | 0.5966 | 0.4105 | 0.5966 | 0.7724 |
| No log | 4.1860 | 180 | 0.6502 | 0.3061 | 0.6502 | 0.8063 |
| No log | 4.2326 | 182 | 0.6416 | 0.3061 | 0.6416 | 0.8010 |
| No log | 4.2791 | 184 | 0.8263 | 0.1933 | 0.8263 | 0.9090 |
| No log | 4.3256 | 186 | 0.8510 | 0.1613 | 0.8510 | 0.9225 |
| No log | 4.3721 | 188 | 0.7406 | 0.2838 | 0.7406 | 0.8606 |
| No log | 4.4186 | 190 | 0.5744 | 0.4112 | 0.5744 | 0.7579 |
| No log | 4.4651 | 192 | 0.6133 | 0.3448 | 0.6133 | 0.7831 |
| No log | 4.5116 | 194 | 0.5839 | 0.3527 | 0.5839 | 0.7641 |
| No log | 4.5581 | 196 | 0.6697 | 0.3761 | 0.6697 | 0.8184 |
| No log | 4.6047 | 198 | 1.0358 | 0.1886 | 1.0358 | 1.0178 |
| No log | 4.6512 | 200 | 1.0502 | 0.1942 | 1.0502 | 1.0248 |
| No log | 4.6977 | 202 | 0.7390 | 0.3684 | 0.7390 | 0.8597 |
| No log | 4.7442 | 204 | 0.5410 | 0.4286 | 0.5410 | 0.7355 |
| No log | 4.7907 | 206 | 0.5180 | 0.4462 | 0.5180 | 0.7197 |
| No log | 4.8372 | 208 | 0.5897 | 0.36 | 0.5897 | 0.7679 |
| No log | 4.8837 | 210 | 0.6374 | 0.3645 | 0.6374 | 0.7984 |
| No log | 4.9302 | 212 | 0.5391 | 0.3939 | 0.5391 | 0.7342 |
| No log | 4.9767 | 214 | 0.4812 | 0.4348 | 0.4812 | 0.6937 |
| No log | 5.0233 | 216 | 0.5044 | 0.3661 | 0.5044 | 0.7102 |
| No log | 5.0698 | 218 | 0.4712 | 0.3757 | 0.4712 | 0.6864 |
| No log | 5.1163 | 220 | 0.5424 | 0.2990 | 0.5424 | 0.7365 |
| No log | 5.1628 | 222 | 0.5456 | 0.2990 | 0.5456 | 0.7387 |
| No log | 5.2093 | 224 | 0.4782 | 0.3455 | 0.4782 | 0.6915 |
| No log | 5.2558 | 226 | 0.5155 | 0.3488 | 0.5155 | 0.7180 |
| No log | 5.3023 | 228 | 0.5230 | 0.3054 | 0.5230 | 0.7232 |
| No log | 5.3488 | 230 | 0.4920 | 0.3563 | 0.4920 | 0.7014 |
| No log | 5.3953 | 232 | 0.5155 | 0.3617 | 0.5155 | 0.7180 |
| No log | 5.4419 | 234 | 0.5495 | 0.4231 | 0.5495 | 0.7413 |
| No log | 5.4884 | 236 | 0.5024 | 0.4123 | 0.5024 | 0.7088 |
| No log | 5.5349 | 238 | 0.5127 | 0.4231 | 0.5127 | 0.7160 |
| No log | 5.5814 | 240 | 0.5155 | 0.4175 | 0.5155 | 0.7180 |
| No log | 5.6279 | 242 | 0.5296 | 0.4286 | 0.5296 | 0.7278 |
| No log | 5.6744 | 244 | 0.6400 | 0.3874 | 0.6400 | 0.8000 |
| No log | 5.7209 | 246 | 0.6637 | 0.3571 | 0.6637 | 0.8147 |
| No log | 5.7674 | 248 | 0.5776 | 0.2088 | 0.5776 | 0.7600 |
| No log | 5.8140 | 250 | 0.5070 | 0.3563 | 0.5070 | 0.7120 |
| No log | 5.8605 | 252 | 0.5893 | 0.3520 | 0.5893 | 0.7676 |
| No log | 5.9070 | 254 | 0.5546 | 0.2941 | 0.5546 | 0.7447 |
| No log | 5.9535 | 256 | 0.5304 | 0.4023 | 0.5304 | 0.7283 |
| No log | 6.0 | 258 | 0.6739 | 0.2676 | 0.6739 | 0.8209 |
| No log | 6.0465 | 260 | 0.7533 | 0.3004 | 0.7533 | 0.8679 |
| No log | 6.0930 | 262 | 0.7068 | 0.3028 | 0.7068 | 0.8407 |
| No log | 6.1395 | 264 | 0.5518 | 0.3831 | 0.5518 | 0.7428 |
| No log | 6.1860 | 266 | 0.5005 | 0.4536 | 0.5005 | 0.7074 |
| No log | 6.2326 | 268 | 0.4944 | 0.4667 | 0.4944 | 0.7031 |
| No log | 6.2791 | 270 | 0.5255 | 0.3508 | 0.5255 | 0.7249 |
| No log | 6.3256 | 272 | 0.6078 | 0.3333 | 0.6078 | 0.7796 |
| No log | 6.3721 | 274 | 0.6965 | 0.3274 | 0.6965 | 0.8346 |
| No log | 6.4186 | 276 | 0.6523 | 0.3035 | 0.6523 | 0.8076 |
| No log | 6.4651 | 278 | 0.6032 | 0.2688 | 0.6032 | 0.7767 |
| No log | 6.5116 | 280 | 0.5245 | 0.3939 | 0.5245 | 0.7242 |
| No log | 6.5581 | 282 | 0.4952 | 0.3208 | 0.4952 | 0.7037 |
| No log | 6.6047 | 284 | 0.5030 | 0.35 | 0.5030 | 0.7092 |
| No log | 6.6512 | 286 | 0.5329 | 0.3711 | 0.5329 | 0.7300 |
| No log | 6.6977 | 288 | 0.5395 | 0.3659 | 0.5395 | 0.7345 |
| No log | 6.7442 | 290 | 0.5496 | 0.3292 | 0.5496 | 0.7414 |
| No log | 6.7907 | 292 | 0.5301 | 0.3659 | 0.5301 | 0.7281 |
| No log | 6.8372 | 294 | 0.5584 | 0.3659 | 0.5584 | 0.7473 |
| No log | 6.8837 | 296 | 0.5322 | 0.4491 | 0.5322 | 0.7295 |
| No log | 6.9302 | 298 | 0.5342 | 0.4353 | 0.5342 | 0.7309 |
| No log | 6.9767 | 300 | 0.5567 | 0.3533 | 0.5567 | 0.7461 |
| No log | 7.0233 | 302 | 0.5488 | 0.4353 | 0.5488 | 0.7408 |
| No log | 7.0698 | 304 | 0.5705 | 0.3103 | 0.5705 | 0.7553 |
| No log | 7.1163 | 306 | 0.5774 | 0.2626 | 0.5774 | 0.7599 |
| No log | 7.1628 | 308 | 0.5767 | 0.2626 | 0.5767 | 0.7594 |
| No log | 7.2093 | 310 | 0.5545 | 0.3407 | 0.5545 | 0.7447 |
| No log | 7.2558 | 312 | 0.5311 | 0.3548 | 0.5311 | 0.7288 |
| No log | 7.3023 | 314 | 0.5596 | 0.2626 | 0.5596 | 0.7481 |
| No log | 7.3488 | 316 | 0.6035 | 0.2609 | 0.6035 | 0.7768 |
| No log | 7.3953 | 318 | 0.6180 | 0.3016 | 0.6180 | 0.7862 |
| No log | 7.4419 | 320 | 0.5685 | 0.2626 | 0.5685 | 0.7540 |
| No log | 7.4884 | 322 | 0.5469 | 0.2626 | 0.5469 | 0.7395 |
| No log | 7.5349 | 324 | 0.5606 | 0.2626 | 0.5606 | 0.7487 |
| No log | 7.5814 | 326 | 0.5555 | 0.2090 | 0.5555 | 0.7453 |
| No log | 7.6279 | 328 | 0.5497 | 0.2558 | 0.5497 | 0.7414 |
| No log | 7.6744 | 330 | 0.5393 | 0.3371 | 0.5393 | 0.7343 |
| No log | 7.7209 | 332 | 0.5163 | 0.4545 | 0.5163 | 0.7186 |
| No log | 7.7674 | 334 | 0.5056 | 0.4667 | 0.5056 | 0.7111 |
| No log | 7.8140 | 336 | 0.5089 | 0.4286 | 0.5089 | 0.7134 |
| No log | 7.8605 | 338 | 0.5299 | 0.4545 | 0.5299 | 0.7279 |
| No log | 7.9070 | 340 | 0.5764 | 0.1732 | 0.5764 | 0.7592 |
| No log | 7.9535 | 342 | 0.5972 | 0.2688 | 0.5972 | 0.7728 |
| No log | 8.0 | 344 | 0.5877 | 0.2174 | 0.5877 | 0.7666 |
| No log | 8.0465 | 346 | 0.5790 | 0.1724 | 0.5790 | 0.7609 |
| No log | 8.0930 | 348 | 0.5373 | 0.3636 | 0.5373 | 0.7330 |
| No log | 8.1395 | 350 | 0.5119 | 0.4667 | 0.5119 | 0.7155 |
| No log | 8.1860 | 352 | 0.5102 | 0.4286 | 0.5102 | 0.7143 |
| No log | 8.2326 | 354 | 0.5095 | 0.4667 | 0.5095 | 0.7138 |
| No log | 8.2791 | 356 | 0.5360 | 0.3295 | 0.5360 | 0.7322 |
| No log | 8.3256 | 358 | 0.5946 | 0.2670 | 0.5946 | 0.7711 |
| No log | 8.3721 | 360 | 0.5993 | 0.3061 | 0.5993 | 0.7741 |
| No log | 8.4186 | 362 | 0.5560 | 0.2749 | 0.5560 | 0.7456 |
| No log | 8.4651 | 364 | 0.5102 | 0.3810 | 0.5102 | 0.7143 |
| No log | 8.5116 | 366 | 0.4858 | 0.4419 | 0.4858 | 0.6970 |
| No log | 8.5581 | 368 | 0.4825 | 0.4286 | 0.4825 | 0.6946 |
| No log | 8.6047 | 370 | 0.4847 | 0.4802 | 0.4847 | 0.6962 |
| No log | 8.6512 | 372 | 0.4987 | 0.3810 | 0.4987 | 0.7062 |
| No log | 8.6977 | 374 | 0.5199 | 0.3882 | 0.5199 | 0.7211 |
| No log | 8.7442 | 376 | 0.5328 | 0.4146 | 0.5328 | 0.7299 |
| No log | 8.7907 | 378 | 0.5317 | 0.3533 | 0.5317 | 0.7291 |
| No log | 8.8372 | 380 | 0.5283 | 0.3882 | 0.5283 | 0.7269 |
| No log | 8.8837 | 382 | 0.5364 | 0.3533 | 0.5364 | 0.7324 |
| No log | 8.9302 | 384 | 0.5499 | 0.3023 | 0.5499 | 0.7415 |
| No log | 8.9767 | 386 | 0.5569 | 0.3023 | 0.5569 | 0.7462 |
| No log | 9.0233 | 388 | 0.5528 | 0.3023 | 0.5528 | 0.7435 |
| No log | 9.0698 | 390 | 0.5545 | 0.3023 | 0.5545 | 0.7446 |
| No log | 9.1163 | 392 | 0.5723 | 0.3073 | 0.5723 | 0.7565 |
| No log | 9.1628 | 394 | 0.5839 | 0.2265 | 0.5839 | 0.7641 |
| No log | 9.2093 | 396 | 0.5740 | 0.3073 | 0.5740 | 0.7576 |
| No log | 9.2558 | 398 | 0.5585 | 0.2542 | 0.5585 | 0.7473 |
| No log | 9.3023 | 400 | 0.5652 | 0.2542 | 0.5652 | 0.7518 |
| No log | 9.3488 | 402 | 0.5605 | 0.2542 | 0.5605 | 0.7487 |
| No log | 9.3953 | 404 | 0.5626 | 0.2542 | 0.5626 | 0.7500 |
| No log | 9.4419 | 406 | 0.5723 | 0.3073 | 0.5723 | 0.7565 |
| No log | 9.4884 | 408 | 0.5715 | 0.3103 | 0.5715 | 0.7560 |
| No log | 9.5349 | 410 | 0.5641 | 0.2542 | 0.5641 | 0.7510 |
| No log | 9.5814 | 412 | 0.5559 | 0.2889 | 0.5559 | 0.7456 |
| No log | 9.6279 | 414 | 0.5535 | 0.2889 | 0.5535 | 0.7440 |
| No log | 9.6744 | 416 | 0.5548 | 0.2889 | 0.5548 | 0.7448 |
| No log | 9.7209 | 418 | 0.5562 | 0.2542 | 0.5562 | 0.7458 |
| No log | 9.7674 | 420 | 0.5540 | 0.3023 | 0.5540 | 0.7443 |
| No log | 9.8140 | 422 | 0.5533 | 0.3023 | 0.5533 | 0.7438 |
| No log | 9.8605 | 424 | 0.5502 | 0.3371 | 0.5502 | 0.7417 |
| No log | 9.9070 | 426 | 0.5475 | 0.3371 | 0.5475 | 0.7400 |
| No log | 9.9535 | 428 | 0.5465 | 0.3371 | 0.5465 | 0.7392 |
| No log | 10.0 | 430 | 0.5457 | 0.3371 | 0.5457 | 0.7387 |
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/ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k7_task3_organization
Base model
aubmindlab/bert-base-arabertv02