--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task5_fold6 results: [] --- # arabert_cross_relevance_task5_fold6 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: 0.3006 - Qwk: 0.2137 - Mse: 0.3007 ## 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 | 1.0217 | 0.0195 | 1.0225 | | No log | 0.25 | 4 | 0.4152 | 0.0535 | 0.4143 | | No log | 0.375 | 6 | 0.3599 | 0.0454 | 0.3596 | | No log | 0.5 | 8 | 0.3055 | 0.0426 | 0.3056 | | No log | 0.625 | 10 | 0.2854 | 0.0805 | 0.2861 | | No log | 0.75 | 12 | 0.2641 | 0.1393 | 0.2644 | | No log | 0.875 | 14 | 0.2524 | 0.1301 | 0.2527 | | No log | 1.0 | 16 | 0.2428 | 0.1915 | 0.2430 | | No log | 1.125 | 18 | 0.2426 | 0.1915 | 0.2428 | | No log | 1.25 | 20 | 0.2443 | 0.1915 | 0.2447 | | No log | 1.375 | 22 | 0.2471 | 0.1854 | 0.2474 | | No log | 1.5 | 24 | 0.2514 | 0.1890 | 0.2517 | | No log | 1.625 | 26 | 0.2516 | 0.1638 | 0.2519 | | No log | 1.75 | 28 | 0.2545 | 0.1467 | 0.2547 | | No log | 1.875 | 30 | 0.2544 | 0.1816 | 0.2547 | | No log | 2.0 | 32 | 0.2492 | 0.2200 | 0.2495 | | No log | 2.125 | 34 | 0.2568 | 0.2044 | 0.2572 | | No log | 2.25 | 36 | 0.2853 | 0.2266 | 0.2857 | | No log | 2.375 | 38 | 0.2827 | 0.2137 | 0.2831 | | No log | 2.5 | 40 | 0.2560 | 0.2018 | 0.2565 | | No log | 2.625 | 42 | 0.2538 | 0.2177 | 0.2543 | | No log | 2.75 | 44 | 0.2538 | 0.1854 | 0.2542 | | No log | 2.875 | 46 | 0.2581 | 0.2064 | 0.2584 | | No log | 3.0 | 48 | 0.2645 | 0.2064 | 0.2648 | | No log | 3.125 | 50 | 0.2629 | 0.1830 | 0.2631 | | No log | 3.25 | 52 | 0.2615 | 0.1539 | 0.2618 | | No log | 3.375 | 54 | 0.2644 | 0.1588 | 0.2646 | | No log | 3.5 | 56 | 0.2734 | 0.2119 | 0.2736 | | No log | 3.625 | 58 | 0.2799 | 0.2050 | 0.2801 | | No log | 3.75 | 60 | 0.2702 | 0.2050 | 0.2704 | | No log | 3.875 | 62 | 0.2549 | 0.1999 | 0.2553 | | No log | 4.0 | 64 | 0.2524 | 0.2274 | 0.2528 | | No log | 4.125 | 66 | 0.2506 | 0.2274 | 0.2510 | | No log | 4.25 | 68 | 0.2560 | 0.1999 | 0.2563 | | No log | 4.375 | 70 | 0.2850 | 0.2194 | 0.2853 | | No log | 4.5 | 72 | 0.3006 | 0.2282 | 0.3008 | | No log | 4.625 | 74 | 0.2929 | 0.2099 | 0.2931 | | No log | 4.75 | 76 | 0.2761 | 0.2109 | 0.2764 | | No log | 4.875 | 78 | 0.2669 | 0.2119 | 0.2671 | | No log | 5.0 | 80 | 0.2664 | 0.2057 | 0.2667 | | No log | 5.125 | 82 | 0.2687 | 0.2109 | 0.2689 | | No log | 5.25 | 84 | 0.2617 | 0.2109 | 0.2619 | | No log | 5.375 | 86 | 0.2588 | 0.2109 | 0.2590 | | No log | 5.5 | 88 | 0.2627 | 0.2050 | 0.2628 | | No log | 5.625 | 90 | 0.2860 | 0.2147 | 0.2861 | | No log | 5.75 | 92 | 0.3309 | 0.2252 | 0.3309 | | No log | 5.875 | 94 | 0.3340 | 0.2200 | 0.3341 | | No log | 6.0 | 96 | 0.3021 | 0.2083 | 0.3022 | | No log | 6.125 | 98 | 0.2691 | 0.2173 | 0.2694 | | No log | 6.25 | 100 | 0.2601 | 0.2200 | 0.2604 | | No log | 6.375 | 102 | 0.2632 | 0.2173 | 0.2635 | | No log | 6.5 | 104 | 0.2738 | 0.2220 | 0.2741 | | No log | 6.625 | 106 | 0.2881 | 0.2250 | 0.2884 | | No log | 6.75 | 108 | 0.3079 | 0.2127 | 0.3081 | | No log | 6.875 | 110 | 0.3154 | 0.2170 | 0.3156 | | No log | 7.0 | 112 | 0.3054 | 0.2137 | 0.3056 | | No log | 7.125 | 114 | 0.2897 | 0.2091 | 0.2899 | | No log | 7.25 | 116 | 0.2842 | 0.2044 | 0.2844 | | No log | 7.375 | 118 | 0.2794 | 0.2099 | 0.2796 | | No log | 7.5 | 120 | 0.2789 | 0.2099 | 0.2791 | | No log | 7.625 | 122 | 0.2813 | 0.2099 | 0.2814 | | No log | 7.75 | 124 | 0.2926 | 0.2091 | 0.2927 | | No log | 7.875 | 126 | 0.3068 | 0.2137 | 0.3069 | | No log | 8.0 | 128 | 0.3323 | 0.2118 | 0.3323 | | No log | 8.125 | 130 | 0.3463 | 0.2070 | 0.3463 | | No log | 8.25 | 132 | 0.3382 | 0.2118 | 0.3383 | | No log | 8.375 | 134 | 0.3313 | 0.2118 | 0.3314 | | No log | 8.5 | 136 | 0.3174 | 0.2137 | 0.3174 | | No log | 8.625 | 138 | 0.3049 | 0.2137 | 0.3050 | | No log | 8.75 | 140 | 0.3007 | 0.2137 | 0.3008 | | No log | 8.875 | 142 | 0.2970 | 0.2137 | 0.2971 | | No log | 9.0 | 144 | 0.2949 | 0.2137 | 0.2950 | | No log | 9.125 | 146 | 0.2966 | 0.2137 | 0.2967 | | No log | 9.25 | 148 | 0.2992 | 0.2137 | 0.2994 | | No log | 9.375 | 150 | 0.2997 | 0.2137 | 0.2999 | | No log | 9.5 | 152 | 0.3018 | 0.2137 | 0.3019 | | No log | 9.625 | 154 | 0.3012 | 0.2137 | 0.3013 | | No log | 9.75 | 156 | 0.3004 | 0.2137 | 0.3006 | | No log | 9.875 | 158 | 0.3005 | 0.2137 | 0.3006 | | No log | 10.0 | 160 | 0.3006 | 0.2137 | 0.3007 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1