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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_vocabulary_task1_fold1 |
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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_vocabulary_task1_fold1 |
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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: 0.8237 |
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- Qwk: 0.0005 |
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- Mse: 0.8231 |
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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 | 6.3728 | -0.0031 | 6.3683 | |
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| No log | 0.25 | 4 | 2.4100 | -0.0135 | 2.4074 | |
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| No log | 0.375 | 6 | 0.8300 | 0.0029 | 0.8281 | |
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| No log | 0.5 | 8 | 0.5694 | 0.0422 | 0.5684 | |
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| No log | 0.625 | 10 | 0.5771 | 0.0819 | 0.5758 | |
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| No log | 0.75 | 12 | 0.5787 | 0.0393 | 0.5780 | |
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| No log | 0.875 | 14 | 0.5560 | 0.0075 | 0.5555 | |
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| No log | 1.0 | 16 | 0.5627 | -0.0083 | 0.5623 | |
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| No log | 1.125 | 18 | 0.6677 | 0.0 | 0.6674 | |
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| No log | 1.25 | 20 | 0.7346 | 0.0 | 0.7343 | |
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| No log | 1.375 | 22 | 0.6544 | 0.0 | 0.6540 | |
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| No log | 1.5 | 24 | 0.7414 | 0.0 | 0.7411 | |
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| No log | 1.625 | 26 | 0.7091 | 0.0 | 0.7088 | |
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| No log | 1.75 | 28 | 0.5841 | 0.0 | 0.5836 | |
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| No log | 1.875 | 30 | 0.5323 | 0.0422 | 0.5314 | |
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| No log | 2.0 | 32 | 0.5359 | 0.0488 | 0.5349 | |
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| No log | 2.125 | 34 | 0.5392 | 0.0 | 0.5385 | |
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| No log | 2.25 | 36 | 0.6346 | 0.0 | 0.6342 | |
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| No log | 2.375 | 38 | 0.7730 | 0.0 | 0.7727 | |
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| No log | 2.5 | 40 | 0.7599 | 0.0 | 0.7595 | |
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| No log | 2.625 | 42 | 0.6719 | 0.0 | 0.6714 | |
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| No log | 2.75 | 44 | 0.7595 | 0.0 | 0.7591 | |
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| No log | 2.875 | 46 | 0.8678 | 0.0202 | 0.8675 | |
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| No log | 3.0 | 48 | 0.8677 | 0.0151 | 0.8674 | |
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| No log | 3.125 | 50 | 0.9100 | 0.0193 | 0.9096 | |
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| No log | 3.25 | 52 | 1.2346 | 0.0466 | 1.2345 | |
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| No log | 3.375 | 54 | 1.3974 | 0.1074 | 1.3974 | |
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| No log | 3.5 | 56 | 1.1473 | 0.0657 | 1.1472 | |
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| No log | 3.625 | 58 | 0.7783 | -0.0050 | 0.7779 | |
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| No log | 3.75 | 60 | 0.6393 | 0.0 | 0.6387 | |
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| No log | 3.875 | 62 | 0.6653 | 0.0 | 0.6648 | |
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| No log | 4.0 | 64 | 0.6339 | 0.0 | 0.6334 | |
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| No log | 4.125 | 66 | 0.6583 | 0.0 | 0.6578 | |
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| No log | 4.25 | 68 | 0.7357 | 0.0 | 0.7353 | |
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| No log | 4.375 | 70 | 0.9251 | -0.0269 | 0.9248 | |
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| No log | 4.5 | 72 | 1.0004 | 0.0702 | 1.0001 | |
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| No log | 4.625 | 74 | 1.0757 | 0.0049 | 1.0754 | |
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| No log | 4.75 | 76 | 1.0881 | 0.0049 | 1.0878 | |
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| No log | 4.875 | 78 | 0.8102 | -0.0195 | 0.8097 | |
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| No log | 5.0 | 80 | 0.6847 | 0.0 | 0.6840 | |
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| No log | 5.125 | 82 | 0.7337 | -0.0050 | 0.7331 | |
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| No log | 5.25 | 84 | 0.7008 | 0.0 | 0.7001 | |
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| No log | 5.375 | 86 | 0.7016 | -0.0050 | 0.7009 | |
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| No log | 5.5 | 88 | 0.7481 | -0.0195 | 0.7475 | |
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| No log | 5.625 | 90 | 0.7384 | 0.0051 | 0.7377 | |
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| No log | 5.75 | 92 | 0.7519 | 0.0003 | 0.7511 | |
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| No log | 5.875 | 94 | 0.9434 | 0.0457 | 0.9429 | |
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| No log | 6.0 | 96 | 1.1388 | 0.1084 | 1.1387 | |
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| No log | 6.125 | 98 | 1.1119 | 0.1087 | 1.1118 | |
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| No log | 6.25 | 100 | 0.9851 | 0.0611 | 0.9849 | |
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| No log | 6.375 | 102 | 0.8431 | 0.0327 | 0.8426 | |
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| No log | 6.5 | 104 | 0.7529 | -0.0242 | 0.7523 | |
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| No log | 6.625 | 106 | 0.7658 | -0.0242 | 0.7653 | |
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| No log | 6.75 | 108 | 0.8717 | 0.0376 | 0.8713 | |
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| No log | 6.875 | 110 | 0.9321 | 0.0376 | 0.9319 | |
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| No log | 7.0 | 112 | 0.9103 | 0.0426 | 0.9101 | |
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| No log | 7.125 | 114 | 0.8699 | 0.0193 | 0.8696 | |
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| No log | 7.25 | 116 | 0.7446 | -0.0195 | 0.7440 | |
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| No log | 7.375 | 118 | 0.6938 | -0.0446 | 0.6931 | |
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| No log | 7.5 | 120 | 0.6932 | -0.0446 | 0.6926 | |
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| No log | 7.625 | 122 | 0.7665 | -0.0242 | 0.7659 | |
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| No log | 7.75 | 124 | 0.9012 | -0.0078 | 0.9008 | |
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| No log | 7.875 | 126 | 0.9982 | 0.0480 | 0.9978 | |
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| No log | 8.0 | 128 | 1.0450 | 0.0602 | 1.0446 | |
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| No log | 8.125 | 130 | 1.0164 | 0.0643 | 1.0160 | |
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| No log | 8.25 | 132 | 0.9926 | 0.0728 | 0.9921 | |
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| No log | 8.375 | 134 | 0.9480 | 0.0328 | 0.9475 | |
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| No log | 8.5 | 136 | 0.9640 | 0.0245 | 0.9635 | |
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| No log | 8.625 | 138 | 0.9946 | 0.0501 | 0.9942 | |
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| No log | 8.75 | 140 | 0.9731 | 0.0245 | 0.9727 | |
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| No log | 8.875 | 142 | 0.9147 | 0.0213 | 0.9142 | |
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| No log | 9.0 | 144 | 0.8829 | 0.0177 | 0.8824 | |
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| No log | 9.125 | 146 | 0.8432 | 0.0231 | 0.8426 | |
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| No log | 9.25 | 148 | 0.8012 | 0.0050 | 0.8006 | |
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| No log | 9.375 | 150 | 0.7936 | -0.0182 | 0.7929 | |
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| No log | 9.5 | 152 | 0.7870 | -0.0182 | 0.7863 | |
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| No log | 9.625 | 154 | 0.8001 | 0.0050 | 0.7994 | |
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| No log | 9.75 | 156 | 0.8093 | 0.0050 | 0.8086 | |
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| No log | 9.875 | 158 | 0.8204 | 0.0005 | 0.8198 | |
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| No log | 10.0 | 160 | 0.8237 | 0.0005 | 0.8231 | |
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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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