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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_fold2 |
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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_fold2 |
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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: 0.8384 |
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- Qwk: 0.0355 |
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- Mse: 0.8384 |
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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 | 4.6248 | -0.0324 | 4.6248 | |
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| No log | 0.2353 | 4 | 1.7789 | 0.0201 | 1.7789 | |
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| No log | 0.3529 | 6 | 0.8842 | 0.0565 | 0.8842 | |
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| No log | 0.4706 | 8 | 0.8601 | -0.0731 | 0.8601 | |
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| No log | 0.5882 | 10 | 0.8512 | -0.0838 | 0.8512 | |
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| No log | 0.7059 | 12 | 0.7752 | -0.0229 | 0.7752 | |
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| No log | 0.8235 | 14 | 0.7856 | 0.0496 | 0.7856 | |
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| No log | 0.9412 | 16 | 0.7647 | 0.0550 | 0.7647 | |
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| No log | 1.0588 | 18 | 0.8100 | 0.0 | 0.8100 | |
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| No log | 1.1765 | 20 | 0.9168 | 0.0 | 0.9168 | |
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| No log | 1.2941 | 22 | 0.8569 | 0.0 | 0.8569 | |
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| No log | 1.4118 | 24 | 0.7547 | 0.0 | 0.7547 | |
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| No log | 1.5294 | 26 | 0.7737 | 0.0 | 0.7737 | |
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| No log | 1.6471 | 28 | 0.7574 | 0.0 | 0.7574 | |
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| No log | 1.7647 | 30 | 0.7125 | 0.0550 | 0.7125 | |
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| No log | 1.8824 | 32 | 0.7216 | 0.0 | 0.7216 | |
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| No log | 2.0 | 34 | 1.0254 | -0.0072 | 1.0254 | |
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| No log | 2.1176 | 36 | 1.2005 | 0.1411 | 1.2005 | |
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| No log | 2.2353 | 38 | 1.0049 | -0.0072 | 1.0049 | |
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| No log | 2.3529 | 40 | 0.7418 | 0.0140 | 0.7418 | |
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| No log | 2.4706 | 42 | 0.7130 | 0.0441 | 0.7130 | |
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| No log | 2.5882 | 44 | 0.7791 | 0.0 | 0.7791 | |
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| No log | 2.7059 | 46 | 0.9107 | -0.0072 | 0.9107 | |
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| No log | 2.8235 | 48 | 0.8828 | 0.0 | 0.8828 | |
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| No log | 2.9412 | 50 | 0.7509 | 0.0268 | 0.7509 | |
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| No log | 3.0588 | 52 | 0.7111 | 0.1173 | 0.7111 | |
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| No log | 3.1765 | 54 | 0.7162 | 0.1309 | 0.7162 | |
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| No log | 3.2941 | 56 | 0.7366 | 0.0386 | 0.7366 | |
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| No log | 3.4118 | 58 | 0.8225 | 0.0 | 0.8225 | |
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| No log | 3.5294 | 60 | 0.7895 | -0.0072 | 0.7895 | |
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| No log | 3.6471 | 62 | 0.7926 | -0.0072 | 0.7926 | |
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| No log | 3.7647 | 64 | 0.8031 | -0.0072 | 0.8031 | |
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| No log | 3.8824 | 66 | 0.8109 | 0.0 | 0.8109 | |
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| No log | 4.0 | 68 | 0.7670 | 0.0361 | 0.7670 | |
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| No log | 4.1176 | 70 | 0.7062 | 0.0643 | 0.7062 | |
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| No log | 4.2353 | 72 | 0.6998 | 0.1209 | 0.6998 | |
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| No log | 4.3529 | 74 | 0.7169 | 0.0755 | 0.7169 | |
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| No log | 4.4706 | 76 | 0.8345 | -0.0072 | 0.8345 | |
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| No log | 4.5882 | 78 | 0.9136 | 0.0387 | 0.9136 | |
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| No log | 4.7059 | 80 | 0.8757 | 0.0086 | 0.8757 | |
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| No log | 4.8235 | 82 | 0.8750 | 0.0086 | 0.8750 | |
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| No log | 4.9412 | 84 | 0.8295 | 0.0 | 0.8295 | |
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| No log | 5.0588 | 86 | 0.7644 | 0.0069 | 0.7644 | |
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| No log | 5.1765 | 88 | 0.7883 | 0.0069 | 0.7883 | |
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| No log | 5.2941 | 90 | 0.8861 | 0.1343 | 0.8861 | |
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| No log | 5.4118 | 92 | 0.8567 | -0.0144 | 0.8567 | |
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| No log | 5.5294 | 94 | 0.7787 | 0.0480 | 0.7787 | |
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| No log | 5.6471 | 96 | 0.7991 | 0.0361 | 0.7991 | |
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| No log | 5.7647 | 98 | 0.8546 | 0.0361 | 0.8546 | |
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| No log | 5.8824 | 100 | 0.8059 | 0.0434 | 0.8059 | |
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| No log | 6.0 | 102 | 0.7338 | 0.0846 | 0.7338 | |
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| No log | 6.1176 | 104 | 0.7167 | 0.1209 | 0.7167 | |
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| No log | 6.2353 | 106 | 0.7205 | 0.1209 | 0.7205 | |
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| No log | 6.3529 | 108 | 0.7597 | 0.0707 | 0.7597 | |
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| No log | 6.4706 | 110 | 0.8598 | -0.0136 | 0.8598 | |
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| No log | 6.5882 | 112 | 0.8616 | 0.0376 | 0.8616 | |
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| No log | 6.7059 | 114 | 0.7980 | 0.0940 | 0.7980 | |
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| No log | 6.8235 | 116 | 0.7853 | 0.0940 | 0.7853 | |
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| No log | 6.9412 | 118 | 0.7673 | 0.1027 | 0.7673 | |
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| No log | 7.0588 | 120 | 0.7550 | 0.1069 | 0.7550 | |
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| No log | 7.1765 | 122 | 0.7670 | 0.1027 | 0.7670 | |
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| No log | 7.2941 | 124 | 0.8362 | 0.0822 | 0.8362 | |
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| No log | 7.4118 | 126 | 0.8895 | -0.0054 | 0.8895 | |
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| No log | 7.5294 | 128 | 0.9417 | -0.0470 | 0.9417 | |
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| No log | 7.6471 | 130 | 0.9102 | -0.0406 | 0.9102 | |
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| No log | 7.7647 | 132 | 0.8290 | 0.0355 | 0.8290 | |
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| No log | 7.8824 | 134 | 0.7603 | 0.0736 | 0.7603 | |
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| No log | 8.0 | 136 | 0.7354 | 0.0643 | 0.7354 | |
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| No log | 8.1176 | 138 | 0.7294 | 0.0643 | 0.7294 | |
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| No log | 8.2353 | 140 | 0.7448 | 0.0596 | 0.7448 | |
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| No log | 8.3529 | 142 | 0.7876 | -0.0216 | 0.7876 | |
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| No log | 8.4706 | 144 | 0.8424 | 0.0081 | 0.8424 | |
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| No log | 8.5882 | 146 | 0.8830 | 0.0295 | 0.8830 | |
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| No log | 8.7059 | 148 | 0.8829 | 0.0295 | 0.8829 | |
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| No log | 8.8235 | 150 | 0.8593 | 0.0295 | 0.8593 | |
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| No log | 8.9412 | 152 | 0.8214 | 0.0355 | 0.8214 | |
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| No log | 9.0588 | 154 | 0.7878 | 0.1217 | 0.7878 | |
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| No log | 9.1765 | 156 | 0.7838 | 0.1255 | 0.7838 | |
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| No log | 9.2941 | 158 | 0.7871 | 0.1255 | 0.7871 | |
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| No log | 9.4118 | 160 | 0.7920 | 0.1255 | 0.7920 | |
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| No log | 9.5294 | 162 | 0.7986 | 0.0388 | 0.7986 | |
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| No log | 9.6471 | 164 | 0.8132 | 0.0479 | 0.8132 | |
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| No log | 9.7647 | 166 | 0.8290 | 0.0355 | 0.8290 | |
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| No log | 9.8824 | 168 | 0.8368 | 0.0355 | 0.8368 | |
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| No log | 10.0 | 170 | 0.8384 | 0.0355 | 0.8384 | |
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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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