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---
base_model: sseyf/arabic_summarization_tp
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: NLP_Summerizer
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# NLP_Summerizer
This model is a fine-tuned version of [sseyf/arabic_summarization_tp](https://huggingface.co/sseyf/arabic_summarization_tp) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0451
- Rouge1: 0.179
- Rouge2: 0.0698
- Rougel: 0.1786
- Rougelsum: 0.1783
- Gen Len: 18.8103
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.1625 | 1.0 | 3351 | 0.0636 | 0.1722 | 0.0625 | 0.1723 | 0.1719 | 18.7864 |
| 0.1107 | 2.0 | 6702 | 0.0482 | 0.1816 | 0.0712 | 0.1814 | 0.1808 | 18.8073 |
| 0.09 | 3.0 | 10053 | 0.0451 | 0.179 | 0.0698 | 0.1786 | 0.1783 | 18.8103 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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