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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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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: AraBERT_token_classification_AraEval24_basic_single |
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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_token_classification_AraEval24_basic_single |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8309 |
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- Precision: 0.0558 |
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- Recall: 0.0104 |
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- F1: 0.0175 |
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- Accuracy: 0.8720 |
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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: 8 |
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- eval_batch_size: 8 |
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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 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.5987 | 1.0 | 2830 | 0.7729 | 1.0 | 0.0002 | 0.0004 | 0.8751 | |
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| 0.5694 | 2.0 | 5660 | 0.7337 | 0.0 | 0.0 | 0.0 | 0.8751 | |
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| 0.4944 | 3.0 | 8490 | 0.7180 | 0.0 | 0.0 | 0.0 | 0.8751 | |
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| 0.4569 | 4.0 | 11320 | 0.7157 | 0.0683 | 0.0039 | 0.0073 | 0.8746 | |
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| 0.4453 | 5.0 | 14150 | 0.7393 | 0.0973 | 0.0063 | 0.0119 | 0.8745 | |
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| 0.3859 | 6.0 | 16980 | 0.7607 | 0.0694 | 0.0042 | 0.0080 | 0.8745 | |
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| 0.3847 | 7.0 | 19810 | 0.7712 | 0.0838 | 0.0074 | 0.0136 | 0.8742 | |
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| 0.3582 | 8.0 | 22640 | 0.7805 | 0.0462 | 0.0081 | 0.0138 | 0.8723 | |
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| 0.3368 | 9.0 | 25470 | 0.8114 | 0.0542 | 0.0078 | 0.0136 | 0.8727 | |
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| 0.3185 | 10.0 | 28300 | 0.8309 | 0.0558 | 0.0104 | 0.0175 | 0.8720 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.13.3 |
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