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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_back_translation_mlm1k_augmented |
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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_back_translation_mlm1k_augmented |
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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: 0.9905 |
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- Precision: 0.0511 |
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- Recall: 0.0181 |
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- F1: 0.0267 |
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- Accuracy: 0.8621 |
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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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| 0.4984 | 1.0 | 7951 | 0.7412 | 0.0194 | 0.0011 | 0.0020 | 0.8715 | |
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| 0.4115 | 2.0 | 15902 | 0.7585 | 0.0571 | 0.0035 | 0.0066 | 0.8721 | |
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| 0.3718 | 3.0 | 23853 | 0.7859 | 0.0720 | 0.0049 | 0.0092 | 0.8724 | |
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| 0.3331 | 4.0 | 31804 | 0.8117 | 0.0431 | 0.0062 | 0.0108 | 0.8679 | |
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| 0.3017 | 5.0 | 39755 | 0.8332 | 0.0477 | 0.0097 | 0.0161 | 0.8658 | |
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| 0.2682 | 6.0 | 47706 | 0.8462 | 0.0540 | 0.0123 | 0.0200 | 0.8628 | |
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| 0.2627 | 7.0 | 55657 | 0.8597 | 0.0553 | 0.0125 | 0.0204 | 0.8636 | |
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| 0.2372 | 8.0 | 63608 | 0.9231 | 0.0556 | 0.0149 | 0.0236 | 0.8646 | |
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| 0.2208 | 9.0 | 71559 | 0.9553 | 0.0567 | 0.0160 | 0.0250 | 0.8657 | |
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| 0.2206 | 10.0 | 79510 | 0.9905 | 0.0511 | 0.0181 | 0.0267 | 0.8621 | |
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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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