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update model card README.md
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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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model-index:
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- name: AraBERT-finetuned-CrossVal-fnd
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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-finetuned-CrossVal-fnd
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2667
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- Macro F1: 0.8831
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- Accuracy: 0.8867
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- Precision: 0.8826
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- Recall: 0.8837
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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: 32
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- seed: 123
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Accuracy | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|
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| 0.296 | 1.0 | 798 | 0.2754 | 0.8729 | 0.8786 | 0.8795 | 0.8684 |
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| 0.2126 | 2.0 | 1596 | 0.2667 | 0.8831 | 0.8867 | 0.8826 | 0.8837 |
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| 0.1719 | 3.0 | 2394 | 0.3204 | 0.8780 | 0.8815 | 0.8768 | 0.8794 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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