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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