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--- |
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base_model: aubmindlab/bert-base-arabertv02 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: arabert_cross_relevance_task2_fold0 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# arabert_cross_relevance_task2_fold0 |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2763 |
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- Qwk: 0.2118 |
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- Mse: 0.2766 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
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| No log | 0.1333 | 2 | 1.2789 | 0.0139 | 1.2791 | |
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| No log | 0.2667 | 4 | 0.3957 | 0.0518 | 0.3957 | |
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| No log | 0.4 | 6 | 0.5497 | 0.0762 | 0.5494 | |
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| No log | 0.5333 | 8 | 0.5310 | 0.0791 | 0.5312 | |
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| No log | 0.6667 | 10 | 0.5062 | 0.0963 | 0.5067 | |
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| No log | 0.8 | 12 | 0.3143 | 0.0865 | 0.3147 | |
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| No log | 0.9333 | 14 | 0.2566 | 0.0879 | 0.2569 | |
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| No log | 1.0667 | 16 | 0.2346 | 0.1763 | 0.2348 | |
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| No log | 1.2 | 18 | 0.2326 | 0.0874 | 0.2328 | |
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| No log | 1.3333 | 20 | 0.2515 | 0.0751 | 0.2516 | |
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| No log | 1.4667 | 22 | 0.2770 | 0.0808 | 0.2772 | |
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| No log | 1.6 | 24 | 0.2829 | 0.0971 | 0.2832 | |
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| No log | 1.7333 | 26 | 0.2820 | 0.1185 | 0.2824 | |
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| No log | 1.8667 | 28 | 0.2898 | 0.2415 | 0.2901 | |
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| No log | 2.0 | 30 | 0.2955 | 0.2956 | 0.2958 | |
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| No log | 2.1333 | 32 | 0.2854 | 0.1934 | 0.2857 | |
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| No log | 2.2667 | 34 | 0.2936 | 0.1068 | 0.2939 | |
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| No log | 2.4 | 36 | 0.2771 | 0.1149 | 0.2775 | |
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| No log | 2.5333 | 38 | 0.2646 | 0.1251 | 0.2649 | |
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| No log | 2.6667 | 40 | 0.2813 | 0.0925 | 0.2816 | |
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| No log | 2.8 | 42 | 0.3144 | 0.0962 | 0.3148 | |
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| No log | 2.9333 | 44 | 0.2730 | 0.1160 | 0.2734 | |
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| No log | 3.0667 | 46 | 0.2608 | 0.1750 | 0.2611 | |
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| No log | 3.2 | 48 | 0.2707 | 0.2039 | 0.2710 | |
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| No log | 3.3333 | 50 | 0.2810 | 0.1280 | 0.2814 | |
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| No log | 3.4667 | 52 | 0.2855 | 0.1188 | 0.2859 | |
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| No log | 3.6 | 54 | 0.2726 | 0.1072 | 0.2730 | |
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| No log | 3.7333 | 56 | 0.2684 | 0.1361 | 0.2688 | |
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| No log | 3.8667 | 58 | 0.2683 | 0.1868 | 0.2686 | |
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| No log | 4.0 | 60 | 0.2781 | 0.2062 | 0.2785 | |
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| No log | 4.1333 | 62 | 0.2921 | 0.2414 | 0.2924 | |
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| No log | 4.2667 | 64 | 0.2977 | 0.2919 | 0.2980 | |
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| No log | 4.4 | 66 | 0.2977 | 0.2571 | 0.2980 | |
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| No log | 4.5333 | 68 | 0.2869 | 0.2312 | 0.2872 | |
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| No log | 4.6667 | 70 | 0.2721 | 0.2289 | 0.2724 | |
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| No log | 4.8 | 72 | 0.2696 | 0.2253 | 0.2699 | |
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| No log | 4.9333 | 74 | 0.2755 | 0.1581 | 0.2759 | |
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| No log | 5.0667 | 76 | 0.2782 | 0.1567 | 0.2786 | |
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| No log | 5.2 | 78 | 0.2752 | 0.1686 | 0.2756 | |
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| No log | 5.3333 | 80 | 0.2765 | 0.1716 | 0.2769 | |
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| No log | 5.4667 | 82 | 0.2686 | 0.2142 | 0.2690 | |
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| No log | 5.6 | 84 | 0.2667 | 0.2265 | 0.2670 | |
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| No log | 5.7333 | 86 | 0.2752 | 0.2050 | 0.2756 | |
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| No log | 5.8667 | 88 | 0.2867 | 0.1803 | 0.2871 | |
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| No log | 6.0 | 90 | 0.2816 | 0.2116 | 0.2819 | |
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| No log | 6.1333 | 92 | 0.2723 | 0.2557 | 0.2726 | |
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| No log | 6.2667 | 94 | 0.2733 | 0.2884 | 0.2735 | |
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| No log | 6.4 | 96 | 0.2753 | 0.2629 | 0.2755 | |
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| No log | 6.5333 | 98 | 0.2787 | 0.2101 | 0.2790 | |
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| No log | 6.6667 | 100 | 0.2860 | 0.1805 | 0.2863 | |
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| No log | 6.8 | 102 | 0.2870 | 0.1727 | 0.2873 | |
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| No log | 6.9333 | 104 | 0.2680 | 0.1702 | 0.2683 | |
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| No log | 7.0667 | 106 | 0.2577 | 0.1767 | 0.2579 | |
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| No log | 7.2 | 108 | 0.2595 | 0.1735 | 0.2598 | |
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| No log | 7.3333 | 110 | 0.2638 | 0.1751 | 0.2640 | |
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| No log | 7.4667 | 112 | 0.2779 | 0.1759 | 0.2782 | |
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| No log | 7.6 | 114 | 0.2860 | 0.1726 | 0.2864 | |
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| No log | 7.7333 | 116 | 0.2810 | 0.1757 | 0.2813 | |
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| No log | 7.8667 | 118 | 0.2683 | 0.1912 | 0.2686 | |
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| No log | 8.0 | 120 | 0.2616 | 0.2129 | 0.2618 | |
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| No log | 8.1333 | 122 | 0.2606 | 0.2129 | 0.2608 | |
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| No log | 8.2667 | 124 | 0.2651 | 0.2043 | 0.2654 | |
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| No log | 8.4 | 126 | 0.2700 | 0.1970 | 0.2703 | |
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| No log | 8.5333 | 128 | 0.2737 | 0.1914 | 0.2741 | |
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| No log | 8.6667 | 130 | 0.2727 | 0.2139 | 0.2731 | |
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| No log | 8.8 | 132 | 0.2748 | 0.2139 | 0.2751 | |
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| No log | 8.9333 | 134 | 0.2738 | 0.2175 | 0.2741 | |
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| No log | 9.0667 | 136 | 0.2726 | 0.2112 | 0.2730 | |
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| No log | 9.2 | 138 | 0.2719 | 0.2166 | 0.2722 | |
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| No log | 9.3333 | 140 | 0.2710 | 0.2275 | 0.2713 | |
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| No log | 9.4667 | 142 | 0.2714 | 0.2275 | 0.2717 | |
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| No log | 9.6 | 144 | 0.2724 | 0.2242 | 0.2727 | |
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| No log | 9.7333 | 146 | 0.2742 | 0.2154 | 0.2745 | |
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| No log | 9.8667 | 148 | 0.2755 | 0.2118 | 0.2758 | |
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| No log | 10.0 | 150 | 0.2763 | 0.2118 | 0.2766 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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