--- library_name: transformers base_model: aubmindlab/bert-base-arabert tags: - generated_from_trainer metrics: - accuracy model-index: - name: arabic-hs-2class-prediction results: [] --- # arabic-hs-2class-prediction This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6540 - Accuracy: 0.8442 - Macro F1: 0.8331 ## 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: 5e-06 - train_batch_size: 16 - eval_batch_size: 20 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:| | 0.6218 | 0.1083 | 100 | 0.5720 | 0.6917 | 0.5951 | | 0.5615 | 0.2167 | 200 | 0.5156 | 0.7297 | 0.6866 | | 0.5132 | 0.3250 | 300 | 0.4785 | 0.7554 | 0.7400 | | 0.4878 | 0.4334 | 400 | 0.4444 | 0.7879 | 0.7657 | | 0.4623 | 0.5417 | 500 | 0.4162 | 0.8049 | 0.7858 | | 0.4643 | 0.6501 | 600 | 0.4030 | 0.8042 | 0.7923 | | 0.4455 | 0.7584 | 700 | 0.4118 | 0.8178 | 0.7969 | | 0.4406 | 0.8667 | 800 | 0.3787 | 0.8320 | 0.8176 | | 0.4145 | 0.9751 | 900 | 0.3786 | 0.8252 | 0.8136 | | 0.4014 | 1.0834 | 1000 | 0.3790 | 0.8340 | 0.8174 | | 0.3784 | 1.1918 | 1100 | 0.3703 | 0.8401 | 0.8285 | | 0.3858 | 1.3001 | 1200 | 0.3651 | 0.8388 | 0.8290 | | 0.3721 | 1.4085 | 1300 | 0.3605 | 0.8435 | 0.8323 | | 0.3836 | 1.5168 | 1400 | 0.3604 | 0.8394 | 0.8312 | | 0.3645 | 1.6251 | 1500 | 0.3658 | 0.8489 | 0.8343 | | 0.375 | 1.7335 | 1600 | 0.3790 | 0.8347 | 0.8144 | | 0.3909 | 1.8418 | 1700 | 0.3526 | 0.8469 | 0.8374 | | 0.3566 | 1.9502 | 1800 | 0.3701 | 0.8482 | 0.8300 | | 0.3243 | 2.0585 | 1900 | 0.3598 | 0.8388 | 0.8310 | | 0.3699 | 2.1668 | 2000 | 0.3753 | 0.8340 | 0.8108 | | 0.32 | 2.2752 | 2100 | 0.3541 | 0.8523 | 0.8408 | | 0.2987 | 2.3835 | 2200 | 0.3588 | 0.8469 | 0.8370 | | 0.3037 | 2.4919 | 2300 | 0.3687 | 0.8523 | 0.8398 | | 0.3156 | 2.6002 | 2400 | 0.3522 | 0.8469 | 0.8378 | | 0.3352 | 2.7086 | 2500 | 0.3440 | 0.8503 | 0.8415 | | 0.3225 | 2.8169 | 2600 | 0.3490 | 0.8489 | 0.8394 | | 0.3 | 2.9252 | 2700 | 0.3638 | 0.8476 | 0.8328 | | 0.2795 | 3.0336 | 2800 | 0.3904 | 0.8482 | 0.8334 | | 0.2787 | 3.1419 | 2900 | 0.4356 | 0.8415 | 0.8194 | | 0.2733 | 3.2503 | 3000 | 0.3792 | 0.8530 | 0.8435 | | 0.2765 | 3.3586 | 3100 | 0.3700 | 0.8496 | 0.8412 | | 0.2746 | 3.4670 | 3200 | 0.3816 | 0.8476 | 0.8343 | | 0.2823 | 3.5753 | 3300 | 0.3704 | 0.8503 | 0.8374 | | 0.2726 | 3.6836 | 3400 | 0.3795 | 0.8516 | 0.8406 | | 0.2661 | 3.7920 | 3500 | 0.4218 | 0.8469 | 0.8283 | | 0.265 | 3.9003 | 3600 | 0.3852 | 0.8523 | 0.8425 | | 0.2686 | 4.0087 | 3700 | 0.3782 | 0.8516 | 0.8428 | | 0.2173 | 4.1170 | 3800 | 0.4008 | 0.8496 | 0.8401 | | 0.2404 | 4.2254 | 3900 | 0.4072 | 0.8577 | 0.8453 | | 0.2635 | 4.3337 | 4000 | 0.3811 | 0.8564 | 0.8464 | | 0.1983 | 4.4420 | 4100 | 0.4038 | 0.8598 | 0.8506 | | 0.2512 | 4.5504 | 4200 | 0.4228 | 0.8482 | 0.8343 | | 0.2375 | 4.6587 | 4300 | 0.4070 | 0.8476 | 0.8359 | | 0.2405 | 4.7671 | 4400 | 0.4433 | 0.8415 | 0.8242 | | 0.2319 | 4.8754 | 4500 | 0.4176 | 0.8469 | 0.8370 | | 0.2249 | 4.9837 | 4600 | 0.4342 | 0.8462 | 0.8361 | | 0.1937 | 5.0921 | 4700 | 0.4543 | 0.8476 | 0.8369 | | 0.2207 | 5.2004 | 4800 | 0.4553 | 0.8489 | 0.8357 | | 0.1963 | 5.3088 | 4900 | 0.4779 | 0.8489 | 0.8331 | | 0.178 | 5.4171 | 5000 | 0.4590 | 0.8455 | 0.8344 | | 0.175 | 5.5255 | 5100 | 0.4663 | 0.8523 | 0.8421 | | 0.1999 | 5.6338 | 5200 | 0.4733 | 0.8523 | 0.8413 | | 0.2018 | 5.7421 | 5300 | 0.4649 | 0.8523 | 0.8411 | | 0.208 | 5.8505 | 5400 | 0.4617 | 0.8482 | 0.8368 | | 0.2096 | 5.9588 | 5500 | 0.4561 | 0.8482 | 0.8379 | | 0.1972 | 6.0672 | 5600 | 0.5073 | 0.8476 | 0.8331 | | 0.1815 | 6.1755 | 5700 | 0.4908 | 0.8469 | 0.8358 | | 0.1625 | 6.2839 | 5800 | 0.5171 | 0.8435 | 0.8298 | | 0.1869 | 6.3922 | 5900 | 0.5083 | 0.8462 | 0.8346 | | 0.1672 | 6.5005 | 6000 | 0.4982 | 0.8509 | 0.8405 | | 0.1757 | 6.6089 | 6100 | 0.5455 | 0.8462 | 0.8307 | | 0.1505 | 6.7172 | 6200 | 0.5220 | 0.8428 | 0.8313 | | 0.1455 | 6.8256 | 6300 | 0.5378 | 0.8428 | 0.8318 | | 0.2074 | 6.9339 | 6400 | 0.5219 | 0.8442 | 0.8336 | | 0.1551 | 7.0423 | 6500 | 0.5336 | 0.8394 | 0.8287 | | 0.1501 | 7.1506 | 6600 | 0.5581 | 0.8435 | 0.8323 | | 0.167 | 7.2589 | 6700 | 0.5594 | 0.8408 | 0.8290 | | 0.1559 | 7.3673 | 6800 | 0.5704 | 0.8449 | 0.8313 | | 0.1676 | 7.4756 | 6900 | 0.5758 | 0.8455 | 0.8319 | | 0.134 | 7.5840 | 7000 | 0.5662 | 0.8482 | 0.8371 | | 0.1773 | 7.6923 | 7100 | 0.5677 | 0.8435 | 0.8323 | | 0.1328 | 7.8007 | 7200 | 0.5843 | 0.8482 | 0.8363 | | 0.1241 | 7.9090 | 7300 | 0.5901 | 0.8435 | 0.8332 | | 0.1657 | 8.0173 | 7400 | 0.6129 | 0.8374 | 0.8281 | | 0.1348 | 8.1257 | 7500 | 0.6221 | 0.8442 | 0.8340 | | 0.1414 | 8.2340 | 7600 | 0.6272 | 0.8421 | 0.8319 | | 0.1166 | 8.3424 | 7700 | 0.6430 | 0.8428 | 0.8324 | | 0.1648 | 8.4507 | 7800 | 0.6359 | 0.8489 | 0.8376 | | 0.1359 | 8.5590 | 7900 | 0.6338 | 0.8476 | 0.8367 | | 0.16 | 8.6674 | 8000 | 0.6433 | 0.8421 | 0.8293 | | 0.1256 | 8.7757 | 8100 | 0.6438 | 0.8455 | 0.8339 | | 0.1673 | 8.8841 | 8200 | 0.6452 | 0.8428 | 0.8304 | | 0.151 | 8.9924 | 8300 | 0.6377 | 0.8394 | 0.8281 | | 0.1381 | 9.1008 | 8400 | 0.6409 | 0.8442 | 0.8318 | | 0.1199 | 9.2091 | 8500 | 0.6336 | 0.8408 | 0.8303 | | 0.1052 | 9.3174 | 8600 | 0.6434 | 0.8401 | 0.8286 | | 0.14 | 9.4258 | 8700 | 0.6460 | 0.8421 | 0.8310 | | 0.1357 | 9.5341 | 8800 | 0.6503 | 0.8428 | 0.8310 | | 0.1149 | 9.6425 | 8900 | 0.6580 | 0.8428 | 0.8301 | | 0.1486 | 9.7508 | 9000 | 0.6552 | 0.8442 | 0.8322 | | 0.1315 | 9.8592 | 9100 | 0.6518 | 0.8442 | 0.8335 | | 0.1125 | 9.9675 | 9200 | 0.6540 | 0.8442 | 0.8331 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.5.1+cu124 - Datasets 3.3.2 - Tokenizers 0.21.0