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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_task5_fold3 |
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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_task5_fold3 |
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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: 0.3040 |
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- Qwk: 0.0224 |
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- Mse: 0.3040 |
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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 | 0.1176 | 2 | 0.3814 | 0.0319 | 0.3814 | |
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| No log | 0.2353 | 4 | 0.4935 | 0.0934 | 0.4935 | |
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| No log | 0.3529 | 6 | 0.3556 | 0.1346 | 0.3556 | |
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| No log | 0.4706 | 8 | 0.2761 | 0.0 | 0.2761 | |
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| No log | 0.5882 | 10 | 0.3024 | 0.0 | 0.3024 | |
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| No log | 0.7059 | 12 | 0.2997 | -0.0517 | 0.2997 | |
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| No log | 0.8235 | 14 | 0.3140 | -0.1029 | 0.3140 | |
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| No log | 0.9412 | 16 | 0.2979 | -0.0473 | 0.2979 | |
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| No log | 1.0588 | 18 | 0.2994 | 0.0 | 0.2994 | |
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| No log | 1.1765 | 20 | 0.2824 | 0.0 | 0.2824 | |
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| No log | 1.2941 | 22 | 0.2570 | 0.0 | 0.2570 | |
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| No log | 1.4118 | 24 | 0.2638 | -0.0235 | 0.2638 | |
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| No log | 1.5294 | 26 | 0.2681 | -0.0235 | 0.2681 | |
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| No log | 1.6471 | 28 | 0.2587 | -0.0235 | 0.2587 | |
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| No log | 1.7647 | 30 | 0.2781 | 0.0 | 0.2781 | |
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| No log | 1.8824 | 32 | 0.3225 | 0.0 | 0.3225 | |
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| No log | 2.0 | 34 | 0.2895 | 0.0 | 0.2895 | |
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| No log | 2.1176 | 36 | 0.2779 | 0.0 | 0.2779 | |
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| No log | 2.2353 | 38 | 0.2807 | 0.0 | 0.2807 | |
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| No log | 2.3529 | 40 | 0.2808 | 0.0 | 0.2808 | |
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| No log | 2.4706 | 42 | 0.2648 | 0.0 | 0.2648 | |
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| No log | 2.5882 | 44 | 0.2627 | 0.0 | 0.2627 | |
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| No log | 2.7059 | 46 | 0.2723 | 0.0 | 0.2723 | |
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| No log | 2.8235 | 48 | 0.2669 | 0.0 | 0.2669 | |
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| No log | 2.9412 | 50 | 0.2817 | 0.0 | 0.2817 | |
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| No log | 3.0588 | 52 | 0.2862 | 0.0 | 0.2862 | |
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| No log | 3.1765 | 54 | 0.2710 | 0.0 | 0.2710 | |
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| No log | 3.2941 | 56 | 0.2691 | 0.0 | 0.2691 | |
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| No log | 3.4118 | 58 | 0.2758 | 0.0 | 0.2758 | |
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| No log | 3.5294 | 60 | 0.2757 | 0.0 | 0.2757 | |
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| No log | 3.6471 | 62 | 0.2734 | 0.0 | 0.2734 | |
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| No log | 3.7647 | 64 | 0.2619 | 0.0 | 0.2619 | |
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| No log | 3.8824 | 66 | 0.2661 | 0.0 | 0.2661 | |
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| No log | 4.0 | 68 | 0.2833 | 0.0 | 0.2833 | |
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| No log | 4.1176 | 70 | 0.2841 | 0.0 | 0.2841 | |
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| No log | 4.2353 | 72 | 0.2826 | 0.0 | 0.2826 | |
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| No log | 4.3529 | 74 | 0.2721 | 0.0 | 0.2721 | |
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| No log | 4.4706 | 76 | 0.2658 | 0.0 | 0.2658 | |
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| No log | 4.5882 | 78 | 0.2740 | 0.0 | 0.2740 | |
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| No log | 4.7059 | 80 | 0.2745 | 0.0 | 0.2745 | |
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| No log | 4.8235 | 82 | 0.2783 | 0.0 | 0.2783 | |
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| No log | 4.9412 | 84 | 0.2774 | 0.0 | 0.2774 | |
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| No log | 5.0588 | 86 | 0.2885 | 0.0 | 0.2885 | |
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| No log | 5.1765 | 88 | 0.3222 | 0.0 | 0.3222 | |
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| No log | 5.2941 | 90 | 0.3391 | 0.0 | 0.3391 | |
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| No log | 5.4118 | 92 | 0.3189 | 0.0 | 0.3189 | |
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| No log | 5.5294 | 94 | 0.3185 | 0.0224 | 0.3185 | |
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| No log | 5.6471 | 96 | 0.2891 | 0.0 | 0.2891 | |
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| No log | 5.7647 | 98 | 0.2697 | 0.0 | 0.2697 | |
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| No log | 5.8824 | 100 | 0.2703 | 0.0 | 0.2703 | |
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| No log | 6.0 | 102 | 0.2749 | 0.0 | 0.2749 | |
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| No log | 6.1176 | 104 | 0.2900 | 0.0 | 0.2900 | |
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| No log | 6.2353 | 106 | 0.3272 | 0.0 | 0.3272 | |
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| No log | 6.3529 | 108 | 0.3347 | 0.0224 | 0.3347 | |
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| No log | 6.4706 | 110 | 0.3020 | 0.0 | 0.3020 | |
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| No log | 6.5882 | 112 | 0.2731 | 0.0 | 0.2731 | |
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| No log | 6.7059 | 114 | 0.2683 | 0.0 | 0.2683 | |
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| No log | 6.8235 | 116 | 0.2736 | 0.0 | 0.2736 | |
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| No log | 6.9412 | 118 | 0.2940 | 0.0 | 0.2940 | |
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| No log | 7.0588 | 120 | 0.3391 | 0.0224 | 0.3391 | |
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| No log | 7.1765 | 122 | 0.3471 | 0.0224 | 0.3471 | |
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| No log | 7.2941 | 124 | 0.3232 | 0.0224 | 0.3232 | |
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| No log | 7.4118 | 126 | 0.2886 | 0.0 | 0.2886 | |
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| No log | 7.5294 | 128 | 0.2755 | 0.0 | 0.2755 | |
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| No log | 7.6471 | 130 | 0.2736 | 0.0 | 0.2736 | |
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| No log | 7.7647 | 132 | 0.2796 | 0.0 | 0.2796 | |
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| No log | 7.8824 | 134 | 0.2901 | 0.0 | 0.2901 | |
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| No log | 8.0 | 136 | 0.3054 | 0.0224 | 0.3054 | |
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| No log | 8.1176 | 138 | 0.3155 | 0.0224 | 0.3155 | |
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| No log | 8.2353 | 140 | 0.3163 | 0.0224 | 0.3163 | |
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| No log | 8.3529 | 142 | 0.3326 | 0.0224 | 0.3326 | |
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| No log | 8.4706 | 144 | 0.3464 | 0.0224 | 0.3464 | |
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| No log | 8.5882 | 146 | 0.3603 | 0.0123 | 0.3603 | |
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| No log | 8.7059 | 148 | 0.3747 | -0.0057 | 0.3747 | |
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| No log | 8.8235 | 150 | 0.3703 | 0.0123 | 0.3703 | |
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| No log | 8.9412 | 152 | 0.3512 | 0.0224 | 0.3512 | |
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| No log | 9.0588 | 154 | 0.3262 | 0.0224 | 0.3262 | |
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| No log | 9.1765 | 156 | 0.3095 | 0.0224 | 0.3095 | |
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| No log | 9.2941 | 158 | 0.3054 | 0.0224 | 0.3054 | |
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| No log | 9.4118 | 160 | 0.3038 | 0.0224 | 0.3038 | |
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| No log | 9.5294 | 162 | 0.3034 | 0.0224 | 0.3034 | |
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| No log | 9.6471 | 164 | 0.3016 | 0.0224 | 0.3016 | |
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| No log | 9.7647 | 166 | 0.3019 | 0.0224 | 0.3019 | |
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| No log | 9.8824 | 168 | 0.3032 | 0.0224 | 0.3032 | |
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| No log | 10.0 | 170 | 0.3040 | 0.0224 | 0.3040 | |
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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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