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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_task7_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_vocabulary_task7_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: 0.9341 |
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- Qwk: 0.8036 |
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- Mse: 0.9341 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 1 |
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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 | 0.0351 | 2 | 3.7363 | 0.0136 | 3.7363 | |
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| No log | 0.0702 | 4 | 2.3106 | 0.1619 | 2.3106 | |
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| No log | 0.1053 | 6 | 1.8172 | 0.1692 | 1.8172 | |
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| No log | 0.1404 | 8 | 1.6116 | 0.2787 | 1.6116 | |
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| No log | 0.1754 | 10 | 1.8910 | 0.3258 | 1.8910 | |
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| No log | 0.2105 | 12 | 1.8785 | 0.4430 | 1.8785 | |
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| No log | 0.2456 | 14 | 1.8131 | 0.4299 | 1.8131 | |
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| No log | 0.2807 | 16 | 2.0288 | 0.5063 | 2.0288 | |
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| No log | 0.3158 | 18 | 1.6252 | 0.5783 | 1.6252 | |
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| No log | 0.3509 | 20 | 1.4668 | 0.6465 | 1.4668 | |
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| No log | 0.3860 | 22 | 1.1133 | 0.6929 | 1.1133 | |
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| No log | 0.4211 | 24 | 0.8668 | 0.7249 | 0.8668 | |
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| No log | 0.4561 | 26 | 0.9262 | 0.7457 | 0.9262 | |
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| No log | 0.4912 | 28 | 1.0096 | 0.7462 | 1.0096 | |
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| No log | 0.5263 | 30 | 1.0968 | 0.7380 | 1.0968 | |
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| No log | 0.5614 | 32 | 1.1232 | 0.7473 | 1.1232 | |
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| No log | 0.5965 | 34 | 1.1632 | 0.7453 | 1.1632 | |
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| No log | 0.6316 | 36 | 1.1137 | 0.7662 | 1.1137 | |
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| No log | 0.6667 | 38 | 1.0328 | 0.7794 | 1.0328 | |
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| No log | 0.7018 | 40 | 0.8546 | 0.8110 | 0.8546 | |
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| No log | 0.7368 | 42 | 0.7276 | 0.7840 | 0.7276 | |
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| No log | 0.7719 | 44 | 0.6916 | 0.7793 | 0.6916 | |
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| No log | 0.8070 | 46 | 0.7025 | 0.7855 | 0.7025 | |
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| No log | 0.8421 | 48 | 0.7202 | 0.7971 | 0.7202 | |
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| No log | 0.8772 | 50 | 0.7770 | 0.8095 | 0.7770 | |
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| No log | 0.9123 | 52 | 0.8545 | 0.8154 | 0.8545 | |
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| No log | 0.9474 | 54 | 0.9105 | 0.8088 | 0.9105 | |
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| No log | 0.9825 | 56 | 0.9341 | 0.8036 | 0.9341 | |
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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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