--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task2_fold1 results: [] --- # arabert_cross_relevance_task2_fold1 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: 0.2539 - Qwk: 0.0 - Mse: 0.2539 ## 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 | 0.8503 | 0.0176 | 0.8493 | | No log | 0.25 | 4 | 0.3494 | 0.1224 | 0.3496 | | No log | 0.375 | 6 | 0.5004 | 0.0515 | 0.5009 | | No log | 0.5 | 8 | 0.3323 | -0.0164 | 0.3328 | | No log | 0.625 | 10 | 0.3005 | 0.0 | 0.3007 | | No log | 0.75 | 12 | 0.3118 | 0.0122 | 0.3119 | | No log | 0.875 | 14 | 0.3876 | 0.0454 | 0.3880 | | No log | 1.0 | 16 | 0.4447 | -0.0079 | 0.4455 | | No log | 1.125 | 18 | 0.4798 | -0.1341 | 0.4806 | | No log | 1.25 | 20 | 0.5158 | -0.0658 | 0.5166 | | No log | 1.375 | 22 | 0.3941 | -0.0135 | 0.3946 | | No log | 1.5 | 24 | 0.3295 | -0.0042 | 0.3298 | | No log | 1.625 | 26 | 0.3244 | 0.0 | 0.3247 | | No log | 1.75 | 28 | 0.3471 | -0.0164 | 0.3476 | | No log | 1.875 | 30 | 0.3538 | -0.0042 | 0.3543 | | No log | 2.0 | 32 | 0.3130 | 0.0 | 0.3134 | | No log | 2.125 | 34 | 0.2809 | 0.0 | 0.2811 | | No log | 2.25 | 36 | 0.2793 | 0.0 | 0.2795 | | No log | 2.375 | 38 | 0.3047 | 0.0 | 0.3050 | | No log | 2.5 | 40 | 0.3696 | 0.0582 | 0.3702 | | No log | 2.625 | 42 | 0.3992 | 0.1381 | 0.3999 | | No log | 2.75 | 44 | 0.3456 | -0.0172 | 0.3461 | | No log | 2.875 | 46 | 0.2805 | 0.0 | 0.2807 | | No log | 3.0 | 48 | 0.2675 | 0.0 | 0.2675 | | No log | 3.125 | 50 | 0.2713 | 0.0 | 0.2712 | | No log | 3.25 | 52 | 0.2691 | 0.0 | 0.2691 | | No log | 3.375 | 54 | 0.2726 | 0.0 | 0.2727 | | No log | 3.5 | 56 | 0.2951 | 0.0 | 0.2954 | | No log | 3.625 | 58 | 0.3397 | 0.0452 | 0.3402 | | No log | 3.75 | 60 | 0.3175 | 0.0450 | 0.3180 | | No log | 3.875 | 62 | 0.2714 | 0.0 | 0.2716 | | No log | 4.0 | 64 | 0.2574 | 0.0 | 0.2573 | | No log | 4.125 | 66 | 0.2608 | 0.0 | 0.2606 | | No log | 4.25 | 68 | 0.2590 | 0.0 | 0.2590 | | No log | 4.375 | 70 | 0.2813 | 0.0 | 0.2815 | | No log | 4.5 | 72 | 0.3090 | 0.0 | 0.3094 | | No log | 4.625 | 74 | 0.3106 | 0.0 | 0.3110 | | No log | 4.75 | 76 | 0.2951 | 0.0 | 0.2954 | | No log | 4.875 | 78 | 0.2767 | 0.0 | 0.2769 | | No log | 5.0 | 80 | 0.2684 | 0.0 | 0.2685 | | No log | 5.125 | 82 | 0.2825 | 0.0122 | 0.2829 | | No log | 5.25 | 84 | 0.3266 | 0.0746 | 0.3272 | | No log | 5.375 | 86 | 0.3486 | 0.0841 | 0.3493 | | No log | 5.5 | 88 | 0.3299 | 0.0833 | 0.3305 | | No log | 5.625 | 90 | 0.2905 | 0.0245 | 0.2909 | | No log | 5.75 | 92 | 0.2675 | 0.0 | 0.2677 | | No log | 5.875 | 94 | 0.2613 | 0.0 | 0.2614 | | No log | 6.0 | 96 | 0.2609 | 0.0 | 0.2610 | | No log | 6.125 | 98 | 0.2647 | 0.0 | 0.2648 | | No log | 6.25 | 100 | 0.2690 | 0.0 | 0.2692 | | No log | 6.375 | 102 | 0.2672 | 0.0 | 0.2675 | | No log | 6.5 | 104 | 0.2632 | 0.0 | 0.2633 | | No log | 6.625 | 106 | 0.2554 | 0.0 | 0.2554 | | No log | 6.75 | 108 | 0.2637 | 0.0 | 0.2635 | | No log | 6.875 | 110 | 0.2670 | -0.0118 | 0.2667 | | No log | 7.0 | 112 | 0.2544 | 0.0 | 0.2543 | | No log | 7.125 | 114 | 0.2718 | 0.0245 | 0.2720 | | No log | 7.25 | 116 | 0.2966 | 0.0161 | 0.2970 | | No log | 7.375 | 118 | 0.2940 | 0.0161 | 0.2944 | | No log | 7.5 | 120 | 0.2714 | 0.0245 | 0.2717 | | No log | 7.625 | 122 | 0.2558 | 0.0 | 0.2559 | | No log | 7.75 | 124 | 0.2559 | 0.0 | 0.2558 | | No log | 7.875 | 126 | 0.2567 | 0.0 | 0.2565 | | No log | 8.0 | 128 | 0.2560 | 0.0 | 0.2559 | | No log | 8.125 | 130 | 0.2526 | 0.0 | 0.2526 | | No log | 8.25 | 132 | 0.2523 | 0.0 | 0.2524 | | No log | 8.375 | 134 | 0.2528 | 0.0 | 0.2528 | | No log | 8.5 | 136 | 0.2536 | 0.0 | 0.2537 | | No log | 8.625 | 138 | 0.2528 | 0.0 | 0.2529 | | No log | 8.75 | 140 | 0.2516 | 0.0 | 0.2516 | | No log | 8.875 | 142 | 0.2517 | 0.0 | 0.2516 | | No log | 9.0 | 144 | 0.2521 | 0.0 | 0.2521 | | No log | 9.125 | 146 | 0.2526 | 0.0 | 0.2526 | | No log | 9.25 | 148 | 0.2531 | 0.0 | 0.2531 | | No log | 9.375 | 150 | 0.2534 | 0.0 | 0.2534 | | No log | 9.5 | 152 | 0.2534 | 0.0 | 0.2534 | | No log | 9.625 | 154 | 0.2536 | 0.0 | 0.2536 | | No log | 9.75 | 156 | 0.2537 | 0.0 | 0.2538 | | No log | 9.875 | 158 | 0.2538 | 0.0 | 0.2539 | | No log | 10.0 | 160 | 0.2539 | 0.0 | 0.2539 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1