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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_task6_fold4 |
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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_task6_fold4 |
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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: 0.2650 |
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- Qwk: 0.3603 |
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- Mse: 0.2650 |
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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 | 0.125 | 2 | 0.5208 | 0.1951 | 0.5208 | |
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| No log | 0.25 | 4 | 0.5167 | 0.1743 | 0.5167 | |
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| No log | 0.375 | 6 | 0.4163 | 0.2124 | 0.4163 | |
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| No log | 0.5 | 8 | 0.3864 | 0.2931 | 0.3864 | |
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| No log | 0.625 | 10 | 0.3687 | 0.3169 | 0.3687 | |
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| No log | 0.75 | 12 | 0.3018 | 0.3399 | 0.3018 | |
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| No log | 0.875 | 14 | 0.3682 | 0.2424 | 0.3682 | |
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| No log | 1.0 | 16 | 0.4150 | 0.2379 | 0.4150 | |
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| No log | 1.125 | 18 | 0.3832 | 0.2446 | 0.3832 | |
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| No log | 1.25 | 20 | 0.3293 | 0.3301 | 0.3293 | |
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| No log | 1.375 | 22 | 0.2923 | 0.4174 | 0.2923 | |
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| No log | 1.5 | 24 | 0.2780 | 0.3858 | 0.2780 | |
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| No log | 1.625 | 26 | 0.2804 | 0.3481 | 0.2804 | |
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| No log | 1.75 | 28 | 0.2982 | 0.3235 | 0.2982 | |
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| No log | 1.875 | 30 | 0.3255 | 0.3037 | 0.3255 | |
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| No log | 2.0 | 32 | 0.3232 | 0.3223 | 0.3232 | |
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| No log | 2.125 | 34 | 0.3010 | 0.3265 | 0.3010 | |
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| No log | 2.25 | 36 | 0.2972 | 0.3385 | 0.2972 | |
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| No log | 2.375 | 38 | 0.2953 | 0.3744 | 0.2953 | |
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| No log | 2.5 | 40 | 0.2914 | 0.3362 | 0.2914 | |
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| No log | 2.625 | 42 | 0.2775 | 0.3356 | 0.2775 | |
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| No log | 2.75 | 44 | 0.2717 | 0.3488 | 0.2717 | |
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| No log | 2.875 | 46 | 0.2682 | 0.3516 | 0.2682 | |
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| No log | 3.0 | 48 | 0.2717 | 0.3659 | 0.2717 | |
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| No log | 3.125 | 50 | 0.2762 | 0.4330 | 0.2762 | |
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| No log | 3.25 | 52 | 0.2974 | 0.4860 | 0.2974 | |
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| No log | 3.375 | 54 | 0.3155 | 0.4427 | 0.3155 | |
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| No log | 3.5 | 56 | 0.2887 | 0.3242 | 0.2887 | |
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| No log | 3.625 | 58 | 0.2903 | 0.2974 | 0.2903 | |
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| No log | 3.75 | 60 | 0.2966 | 0.3011 | 0.2966 | |
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| No log | 3.875 | 62 | 0.3108 | 0.3189 | 0.3108 | |
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| No log | 4.0 | 64 | 0.3002 | 0.3729 | 0.3002 | |
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| No log | 4.125 | 66 | 0.3025 | 0.4184 | 0.3025 | |
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| No log | 4.25 | 68 | 0.2768 | 0.4398 | 0.2768 | |
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| No log | 4.375 | 70 | 0.2840 | 0.4468 | 0.2840 | |
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| No log | 4.5 | 72 | 0.2805 | 0.4330 | 0.2805 | |
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| No log | 4.625 | 74 | 0.2739 | 0.3745 | 0.2739 | |
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| No log | 4.75 | 76 | 0.2753 | 0.3395 | 0.2753 | |
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| No log | 4.875 | 78 | 0.2722 | 0.3153 | 0.2722 | |
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| No log | 5.0 | 80 | 0.2714 | 0.3164 | 0.2714 | |
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| No log | 5.125 | 82 | 0.2809 | 0.3280 | 0.2809 | |
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| No log | 5.25 | 84 | 0.2844 | 0.3541 | 0.2844 | |
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| No log | 5.375 | 86 | 0.2818 | 0.3541 | 0.2818 | |
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| No log | 5.5 | 88 | 0.2663 | 0.3932 | 0.2663 | |
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| No log | 5.625 | 90 | 0.2624 | 0.3872 | 0.2624 | |
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| No log | 5.75 | 92 | 0.2639 | 0.3941 | 0.2639 | |
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| No log | 5.875 | 94 | 0.2817 | 0.3331 | 0.2817 | |
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| No log | 6.0 | 96 | 0.3073 | 0.3225 | 0.3073 | |
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| No log | 6.125 | 98 | 0.3094 | 0.3274 | 0.3094 | |
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| No log | 6.25 | 100 | 0.2931 | 0.3261 | 0.2931 | |
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| No log | 6.375 | 102 | 0.2777 | 0.3289 | 0.2777 | |
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| No log | 6.5 | 104 | 0.2693 | 0.3611 | 0.2693 | |
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| No log | 6.625 | 106 | 0.2685 | 0.3510 | 0.2685 | |
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| No log | 6.75 | 108 | 0.2718 | 0.3630 | 0.2718 | |
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| No log | 6.875 | 110 | 0.2628 | 0.3742 | 0.2628 | |
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| No log | 7.0 | 112 | 0.2633 | 0.3688 | 0.2633 | |
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| No log | 7.125 | 114 | 0.2771 | 0.3635 | 0.2771 | |
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| No log | 7.25 | 116 | 0.2913 | 0.3936 | 0.2913 | |
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| No log | 7.375 | 118 | 0.2849 | 0.4111 | 0.2849 | |
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| No log | 7.5 | 120 | 0.2790 | 0.4053 | 0.2790 | |
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| No log | 7.625 | 122 | 0.2834 | 0.4053 | 0.2834 | |
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| No log | 7.75 | 124 | 0.2822 | 0.3877 | 0.2822 | |
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| No log | 7.875 | 126 | 0.2858 | 0.3818 | 0.2858 | |
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| No log | 8.0 | 128 | 0.2754 | 0.3690 | 0.2754 | |
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| No log | 8.125 | 130 | 0.2679 | 0.3880 | 0.2679 | |
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| No log | 8.25 | 132 | 0.2657 | 0.4144 | 0.2657 | |
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| No log | 8.375 | 134 | 0.2684 | 0.4198 | 0.2684 | |
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| No log | 8.5 | 136 | 0.2677 | 0.4184 | 0.2677 | |
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| No log | 8.625 | 138 | 0.2659 | 0.4077 | 0.2659 | |
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| No log | 8.75 | 140 | 0.2673 | 0.3853 | 0.2673 | |
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| No log | 8.875 | 142 | 0.2664 | 0.3686 | 0.2664 | |
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| No log | 9.0 | 144 | 0.2685 | 0.3582 | 0.2685 | |
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| No log | 9.125 | 146 | 0.2677 | 0.3582 | 0.2677 | |
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| No log | 9.25 | 148 | 0.2671 | 0.3582 | 0.2671 | |
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| No log | 9.375 | 150 | 0.2663 | 0.3582 | 0.2663 | |
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| No log | 9.5 | 152 | 0.2659 | 0.3526 | 0.2659 | |
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| No log | 9.625 | 154 | 0.2647 | 0.3697 | 0.2647 | |
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| No log | 9.75 | 156 | 0.2651 | 0.3705 | 0.2651 | |
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| No log | 9.875 | 158 | 0.2648 | 0.3705 | 0.2648 | |
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| No log | 10.0 | 160 | 0.2650 | 0.3603 | 0.2650 | |
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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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