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license: apache-2.0 |
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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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- f1 |
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- precision |
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- recall |
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base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca |
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model-index: |
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- name: POEMS-CAMELBERT-CA-RUN4-20-fullDatafreez |
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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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# POEMS-CAMELBERT-CA-RUN4-20-fullDatafreez |
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This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-ca](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2919 |
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- Accuracy: 0.7047 |
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- F1: 0.7047 |
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- Precision: 0.7047 |
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- Recall: 0.7047 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 13 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.1886 | 1.0 | 695 | 1.0872 | 0.5447 | 0.5447 | 0.5447 | 0.5447 | |
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| 1.0357 | 2.0 | 1390 | 1.0129 | 0.5831 | 0.5831 | 0.5831 | 0.5831 | |
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| 0.9067 | 3.0 | 2085 | 1.0089 | 0.5954 | 0.5954 | 0.5954 | 0.5954 | |
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| 0.7858 | 4.0 | 2780 | 0.9204 | 0.6453 | 0.6453 | 0.6453 | 0.6453 | |
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| 0.6709 | 5.0 | 3475 | 0.9971 | 0.6442 | 0.6442 | 0.6442 | 0.6442 | |
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| 0.582 | 6.0 | 4170 | 0.9662 | 0.6739 | 0.6739 | 0.6739 | 0.6739 | |
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| 0.5098 | 7.0 | 4865 | 1.0057 | 0.6855 | 0.6855 | 0.6855 | 0.6855 | |
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| 0.4498 | 8.0 | 5560 | 1.1139 | 0.6851 | 0.6851 | 0.6851 | 0.6851 | |
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| 0.4037 | 9.0 | 6255 | 1.1494 | 0.6862 | 0.6862 | 0.6862 | 0.6862 | |
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| 0.3609 | 10.0 | 6950 | 1.1697 | 0.6996 | 0.6996 | 0.6996 | 0.6996 | |
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| 0.3328 | 11.0 | 7645 | 1.2636 | 0.6967 | 0.6967 | 0.6967 | 0.6967 | |
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| 0.3092 | 12.0 | 8340 | 1.2772 | 0.6956 | 0.6956 | 0.6956 | 0.6956 | |
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| 0.2943 | 13.0 | 9035 | 1.2919 | 0.7047 | 0.7047 | 0.7047 | 0.7047 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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