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--- |
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license: cc-by-nc-3.0 |
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base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca-ner |
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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: bert-base-arabic-camelbert-ca-ner_oknashar |
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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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# bert-base-arabic-camelbert-ca-ner_oknashar |
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This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-ca-ner](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca-ner) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2492 |
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- Precision: 0.7007 |
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- Recall: 0.7475 |
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- F1: 0.7234 |
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- Accuracy: 0.9683 |
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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: 15 |
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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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| 0.1376 | 1.0 | 1357 | 0.1260 | 0.5569 | 0.5220 | 0.5389 | 0.9565 | |
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| 0.0874 | 2.0 | 2714 | 0.1150 | 0.6264 | 0.6198 | 0.6231 | 0.9616 | |
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| 0.0578 | 3.0 | 4071 | 0.1162 | 0.6598 | 0.6567 | 0.6583 | 0.9663 | |
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| 0.0372 | 4.0 | 5428 | 0.1336 | 0.6695 | 0.6837 | 0.6765 | 0.9662 | |
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| 0.0257 | 5.0 | 6785 | 0.1667 | 0.6276 | 0.6989 | 0.6613 | 0.9617 | |
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| 0.0183 | 6.0 | 8142 | 0.1537 | 0.6876 | 0.7258 | 0.7062 | 0.9684 | |
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| 0.0139 | 7.0 | 9499 | 0.1813 | 0.6860 | 0.7258 | 0.7054 | 0.9672 | |
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| 0.0096 | 8.0 | 10856 | 0.1935 | 0.6802 | 0.7165 | 0.6979 | 0.9673 | |
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| 0.0076 | 9.0 | 12213 | 0.1880 | 0.7335 | 0.7270 | 0.7302 | 0.9699 | |
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| 0.005 | 10.0 | 13570 | 0.2266 | 0.7070 | 0.7352 | 0.7209 | 0.9683 | |
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| 0.0041 | 11.0 | 14927 | 0.2340 | 0.7011 | 0.7405 | 0.7202 | 0.9681 | |
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| 0.0032 | 12.0 | 16284 | 0.2335 | 0.7146 | 0.7364 | 0.7253 | 0.9687 | |
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| 0.0031 | 13.0 | 17641 | 0.2461 | 0.7060 | 0.7499 | 0.7273 | 0.9683 | |
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| 0.0027 | 14.0 | 18998 | 0.2421 | 0.7088 | 0.7428 | 0.7254 | 0.9686 | |
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| 0.0015 | 15.0 | 20355 | 0.2492 | 0.7007 | 0.7475 | 0.7234 | 0.9683 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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