--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task1_fold3 results: [] --- # arabert_cross_relevance_task1_fold3 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: 0.2800 - Qwk: 0.4057 - Mse: 0.2800 ## 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 | 0.1333 | 2 | 0.4841 | 0.2229 | 0.4841 | | No log | 0.2667 | 4 | 0.4548 | 0.1951 | 0.4548 | | No log | 0.4 | 6 | 0.3736 | 0.2470 | 0.3736 | | No log | 0.5333 | 8 | 0.3640 | 0.2129 | 0.3640 | | No log | 0.6667 | 10 | 0.3899 | 0.1839 | 0.3899 | | No log | 0.8 | 12 | 0.3649 | 0.1986 | 0.3649 | | No log | 0.9333 | 14 | 0.3192 | 0.3366 | 0.3192 | | No log | 1.0667 | 16 | 0.3134 | 0.3522 | 0.3134 | | No log | 1.2 | 18 | 0.2989 | 0.3399 | 0.2989 | | No log | 1.3333 | 20 | 0.3038 | 0.3248 | 0.3038 | | No log | 1.4667 | 22 | 0.3097 | 0.3239 | 0.3097 | | No log | 1.6 | 24 | 0.2998 | 0.3258 | 0.2998 | | No log | 1.7333 | 26 | 0.2810 | 0.3516 | 0.2810 | | No log | 1.8667 | 28 | 0.2789 | 0.3522 | 0.2789 | | No log | 2.0 | 30 | 0.2800 | 0.3509 | 0.2800 | | No log | 2.1333 | 32 | 0.2906 | 0.3375 | 0.2906 | | No log | 2.2667 | 34 | 0.3124 | 0.2959 | 0.3124 | | No log | 2.4 | 36 | 0.3211 | 0.3784 | 0.3211 | | No log | 2.5333 | 38 | 0.3001 | 0.3428 | 0.3001 | | No log | 2.6667 | 40 | 0.2852 | 0.3575 | 0.2852 | | No log | 2.8 | 42 | 0.2865 | 0.3529 | 0.2865 | | No log | 2.9333 | 44 | 0.2806 | 0.3509 | 0.2806 | | No log | 3.0667 | 46 | 0.2874 | 0.3391 | 0.2874 | | No log | 3.2 | 48 | 0.3047 | 0.3615 | 0.3047 | | No log | 3.3333 | 50 | 0.3111 | 0.3705 | 0.3111 | | No log | 3.4667 | 52 | 0.3016 | 0.3428 | 0.3016 | | No log | 3.6 | 54 | 0.2849 | 0.3391 | 0.2849 | | No log | 3.7333 | 56 | 0.2726 | 0.3502 | 0.2726 | | No log | 3.8667 | 58 | 0.2737 | 0.3515 | 0.2737 | | No log | 4.0 | 60 | 0.2771 | 0.3515 | 0.2771 | | No log | 4.1333 | 62 | 0.2716 | 0.3509 | 0.2716 | | No log | 4.2667 | 64 | 0.2745 | 0.3480 | 0.2745 | | No log | 4.4 | 66 | 0.2815 | 0.3431 | 0.2815 | | No log | 4.5333 | 68 | 0.2772 | 0.3599 | 0.2772 | | No log | 4.6667 | 70 | 0.2685 | 0.3637 | 0.2685 | | No log | 4.8 | 72 | 0.2627 | 0.3536 | 0.2627 | | No log | 4.9333 | 74 | 0.2621 | 0.3549 | 0.2621 | | No log | 5.0667 | 76 | 0.2604 | 0.3640 | 0.2604 | | No log | 5.2 | 78 | 0.2644 | 0.3909 | 0.2644 | | No log | 5.3333 | 80 | 0.2834 | 0.4063 | 0.2834 | | No log | 5.4667 | 82 | 0.2855 | 0.3857 | 0.2855 | | No log | 5.6 | 84 | 0.2777 | 0.3709 | 0.2777 | | No log | 5.7333 | 86 | 0.2703 | 0.3543 | 0.2703 | | No log | 5.8667 | 88 | 0.2731 | 0.3495 | 0.2731 | | No log | 6.0 | 90 | 0.2756 | 0.3509 | 0.2756 | | No log | 6.1333 | 92 | 0.2782 | 0.3538 | 0.2782 | | No log | 6.2667 | 94 | 0.2856 | 0.3720 | 0.2856 | | No log | 6.4 | 96 | 0.2950 | 0.4113 | 0.2950 | | No log | 6.5333 | 98 | 0.3066 | 0.4735 | 0.3066 | | No log | 6.6667 | 100 | 0.2982 | 0.4566 | 0.2982 | | No log | 6.8 | 102 | 0.2915 | 0.4196 | 0.2915 | | No log | 6.9333 | 104 | 0.2806 | 0.3842 | 0.2806 | | No log | 7.0667 | 106 | 0.2757 | 0.3868 | 0.2757 | | No log | 7.2 | 108 | 0.2790 | 0.3895 | 0.2790 | | No log | 7.3333 | 110 | 0.2776 | 0.3868 | 0.2776 | | No log | 7.4667 | 112 | 0.2706 | 0.3605 | 0.2706 | | No log | 7.6 | 114 | 0.2683 | 0.3518 | 0.2683 | | No log | 7.7333 | 116 | 0.2688 | 0.3518 | 0.2688 | | No log | 7.8667 | 118 | 0.2706 | 0.3617 | 0.2706 | | No log | 8.0 | 120 | 0.2740 | 0.3712 | 0.2740 | | No log | 8.1333 | 122 | 0.2770 | 0.3712 | 0.2770 | | No log | 8.2667 | 124 | 0.2813 | 0.3756 | 0.2813 | | No log | 8.4 | 126 | 0.2862 | 0.3730 | 0.2862 | | No log | 8.5333 | 128 | 0.2926 | 0.4157 | 0.2926 | | No log | 8.6667 | 130 | 0.2956 | 0.4209 | 0.2956 | | No log | 8.8 | 132 | 0.2928 | 0.4211 | 0.2928 | | No log | 8.9333 | 134 | 0.2870 | 0.4052 | 0.2870 | | No log | 9.0667 | 136 | 0.2834 | 0.3945 | 0.2834 | | No log | 9.2 | 138 | 0.2828 | 0.4002 | 0.2828 | | No log | 9.3333 | 140 | 0.2815 | 0.3952 | 0.2815 | | No log | 9.4667 | 142 | 0.2814 | 0.4057 | 0.2814 | | No log | 9.6 | 144 | 0.2807 | 0.4057 | 0.2807 | | No log | 9.7333 | 146 | 0.2801 | 0.4057 | 0.2801 | | No log | 9.8667 | 148 | 0.2799 | 0.4057 | 0.2799 | | No log | 10.0 | 150 | 0.2800 | 0.4057 | 0.2800 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1