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--- |
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base_model: sseyf/arabic_summarization_tp |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: NLP_Summerizer |
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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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# NLP_Summerizer |
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This model is a fine-tuned version of [sseyf/arabic_summarization_tp](https://huggingface.co/sseyf/arabic_summarization_tp) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0451 |
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- Rouge1: 0.179 |
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- Rouge2: 0.0698 |
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- Rougel: 0.1786 |
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- Rougelsum: 0.1783 |
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- Gen Len: 18.8103 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 0.1625 | 1.0 | 3351 | 0.0636 | 0.1722 | 0.0625 | 0.1723 | 0.1719 | 18.7864 | |
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| 0.1107 | 2.0 | 6702 | 0.0482 | 0.1816 | 0.0712 | 0.1814 | 0.1808 | 18.8073 | |
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| 0.09 | 3.0 | 10053 | 0.0451 | 0.179 | 0.0698 | 0.1786 | 0.1783 | 18.8103 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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