--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task7_fold2 results: [] --- # arabert_cross_relevance_task7_fold2 This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3920 - Qwk: 0.0 - Mse: 0.3925 ## 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: 64 - eval_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:| | No log | 0.125 | 2 | 1.1351 | 0.0055 | 1.1338 | | No log | 0.25 | 4 | 0.3327 | 0.0239 | 0.3327 | | No log | 0.375 | 6 | 0.4966 | 0.0325 | 0.4972 | | No log | 0.5 | 8 | 0.4252 | 0.0068 | 0.4257 | | No log | 0.625 | 10 | 0.3269 | 0.0 | 0.3271 | | No log | 0.75 | 12 | 0.3043 | 0.0 | 0.3043 | | No log | 0.875 | 14 | 0.3478 | -0.0164 | 0.3479 | | No log | 1.0 | 16 | 0.5150 | -0.1231 | 0.5155 | | No log | 1.125 | 18 | 0.6025 | -0.0901 | 0.6032 | | No log | 1.25 | 20 | 0.5883 | -0.1348 | 0.5891 | | No log | 1.375 | 22 | 0.4750 | -0.0759 | 0.4757 | | No log | 1.5 | 24 | 0.3601 | -0.0164 | 0.3606 | | No log | 1.625 | 26 | 0.3455 | 0.0 | 0.3460 | | No log | 1.75 | 28 | 0.3605 | 0.0 | 0.3611 | | No log | 1.875 | 30 | 0.4021 | -0.0875 | 0.4027 | | No log | 2.0 | 32 | 0.4215 | -0.0723 | 0.4221 | | No log | 2.125 | 34 | 0.4273 | -0.1017 | 0.4280 | | No log | 2.25 | 36 | 0.4182 | -0.0723 | 0.4188 | | No log | 2.375 | 38 | 0.3673 | -0.0042 | 0.3677 | | No log | 2.5 | 40 | 0.3484 | 0.0 | 0.3488 | | No log | 2.625 | 42 | 0.3234 | 0.0 | 0.3237 | | No log | 2.75 | 44 | 0.3167 | 0.0 | 0.3170 | | No log | 2.875 | 46 | 0.3171 | 0.0 | 0.3173 | | No log | 3.0 | 48 | 0.3402 | 0.0 | 0.3406 | | No log | 3.125 | 50 | 0.3835 | -0.0462 | 0.3840 | | No log | 3.25 | 52 | 0.3969 | -0.0631 | 0.3975 | | No log | 3.375 | 54 | 0.3965 | -0.0631 | 0.3971 | | No log | 3.5 | 56 | 0.3727 | -0.0085 | 0.3732 | | No log | 3.625 | 58 | 0.3399 | 0.0122 | 0.3403 | | No log | 3.75 | 60 | 0.3210 | 0.0122 | 0.3213 | | No log | 3.875 | 62 | 0.3144 | 0.0122 | 0.3145 | | No log | 4.0 | 64 | 0.3203 | 0.0122 | 0.3205 | | No log | 4.125 | 66 | 0.3278 | 0.0 | 0.3281 | | No log | 4.25 | 68 | 0.3425 | 0.0 | 0.3429 | | No log | 4.375 | 70 | 0.3631 | -0.0085 | 0.3636 | | No log | 4.5 | 72 | 0.3878 | -0.0631 | 0.3884 | | No log | 4.625 | 74 | 0.3841 | -0.0631 | 0.3847 | | No log | 4.75 | 76 | 0.3554 | -0.0164 | 0.3558 | | No log | 4.875 | 78 | 0.3433 | 0.0 | 0.3437 | | No log | 5.0 | 80 | 0.3407 | 0.0 | 0.3410 | | No log | 5.125 | 82 | 0.3450 | 0.0 | 0.3453 | | No log | 5.25 | 84 | 0.3491 | 0.0 | 0.3494 | | No log | 5.375 | 86 | 0.3528 | 0.0 | 0.3532 | | No log | 5.5 | 88 | 0.3559 | 0.0 | 0.3564 | | No log | 5.625 | 90 | 0.3543 | 0.0 | 0.3547 | | No log | 5.75 | 92 | 0.3489 | 0.0 | 0.3493 | | No log | 5.875 | 94 | 0.3478 | 0.0 | 0.3480 | | No log | 6.0 | 96 | 0.3484 | 0.0 | 0.3486 | | No log | 6.125 | 98 | 0.3566 | 0.0 | 0.3568 | | No log | 6.25 | 100 | 0.3544 | 0.0 | 0.3546 | | No log | 6.375 | 102 | 0.3495 | 0.0 | 0.3499 | | No log | 6.5 | 104 | 0.3529 | 0.0 | 0.3534 | | No log | 6.625 | 106 | 0.3633 | 0.0122 | 0.3638 | | No log | 6.75 | 108 | 0.3602 | 0.0122 | 0.3608 | | No log | 6.875 | 110 | 0.3558 | 0.0 | 0.3563 | | No log | 7.0 | 112 | 0.3542 | 0.0 | 0.3548 | | No log | 7.125 | 114 | 0.3543 | 0.0122 | 0.3548 | | No log | 7.25 | 116 | 0.3536 | 0.0122 | 0.3542 | | No log | 7.375 | 118 | 0.3534 | 0.0122 | 0.3539 | | No log | 7.5 | 120 | 0.3538 | 0.0 | 0.3543 | | No log | 7.625 | 122 | 0.3553 | 0.0 | 0.3557 | | No log | 7.75 | 124 | 0.3581 | 0.0 | 0.3585 | | No log | 7.875 | 126 | 0.3601 | 0.0 | 0.3605 | | No log | 8.0 | 128 | 0.3648 | 0.0 | 0.3652 | | No log | 8.125 | 130 | 0.3658 | 0.0 | 0.3662 | | No log | 8.25 | 132 | 0.3655 | 0.0 | 0.3659 | | No log | 8.375 | 134 | 0.3666 | 0.0 | 0.3670 | | No log | 8.5 | 136 | 0.3714 | 0.0 | 0.3718 | | No log | 8.625 | 138 | 0.3763 | 0.0 | 0.3767 | | No log | 8.75 | 140 | 0.3809 | 0.0 | 0.3813 | | No log | 8.875 | 142 | 0.3871 | 0.0 | 0.3875 | | No log | 9.0 | 144 | 0.3938 | 0.0 | 0.3941 | | No log | 9.125 | 146 | 0.3971 | 0.0 | 0.3974 | | No log | 9.25 | 148 | 0.3971 | 0.0 | 0.3975 | | No log | 9.375 | 150 | 0.3950 | 0.0 | 0.3953 | | No log | 9.5 | 152 | 0.3939 | 0.0 | 0.3943 | | No log | 9.625 | 154 | 0.3921 | 0.0 | 0.3925 | | No log | 9.75 | 156 | 0.3913 | 0.0 | 0.3918 | | No log | 9.875 | 158 | 0.3917 | 0.0 | 0.3922 | | No log | 10.0 | 160 | 0.3920 | 0.0 | 0.3925 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1