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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_fixed
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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_fixed
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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: 0.8758
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- Precision: 0.0901
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- Recall: 0.0234
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- F1: 0.0371
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- Accuracy: 0.8606
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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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| 0.6563 | 1.0 | 2851 | 0.7705 | 0.0391 | 0.0006 | 0.0012 | 0.8632 |
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| 0.5865 | 2.0 | 5702 | 0.8071 | 0.0909 | 0.0028 | 0.0055 | 0.8636 |
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| 0.5382 | 3.0 | 8553 | 0.7815 | 0.0578 | 0.0012 | 0.0024 | 0.8634 |
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| 0.5043 | 4.0 | 11404 | 0.7883 | 0.0798 | 0.0021 | 0.0041 | 0.8633 |
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| 0.4445 | 5.0 | 14255 | 0.8188 | 0.0801 | 0.0031 | 0.0060 | 0.8637 |
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| 0.4295 | 6.0 | 17106 | 0.8070 | 0.0877 | 0.0155 | 0.0263 | 0.8610 |
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| 0.4096 | 7.0 | 19957 | 0.8184 | 0.0949 | 0.0135 | 0.0236 | 0.8627 |
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| 0.3827 | 8.0 | 22808 | 0.8362 | 0.0818 | 0.0181 | 0.0296 | 0.8600 |
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| 0.3525 | 9.0 | 25659 | 0.8458 | 0.0893 | 0.0254 | 0.0395 | 0.8599 |
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| 0.3434 | 10.0 | 28510 | 0.8758 | 0.0901 | 0.0234 | 0.0371 | 0.8606 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 1.12.1
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- Datasets 2.13.2
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- Tokenizers 0.13.3
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