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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-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-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: 0.5846
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- Macro F1: 0.7751
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- Accuracy: 0.7803
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- Precision: 0.7740
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- Recall: 0.7767
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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: 25
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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: 5
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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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| 0.5538 | 1.0 | 1597 | 0.5104 | 0.7183 | 0.7352 | 0.7323 | 0.7142 |
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| 0.4689 | 2.0 | 3194 | 0.4849 | 0.7435 | 0.7574 | 0.7551 | 0.7392 |
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| 0.3876 | 3.0 | 4791 | 0.4828 | 0.7693 | 0.7747 | 0.7682 | 0.7708 |
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| 0.3152 | 4.0 | 6388 | 0.5412 | 0.7702 | 0.7747 | 0.7686 | 0.7729 |
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| 0.2627 | 5.0 | 7985 | 0.5846 | 0.7751 | 0.7803 | 0.7740 | 0.7767 |
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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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