---
base_model: malmarjeh/t5-arabic-text-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [malmarjeh/t5-arabic-text-summarization](https://huggingface.co/malmarjeh/t5-arabic-text-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0104
- Rouge1: 0.1382
- Rouge2: 0.0187
- Rougel: 0.1382
- Rougelsum: 0.1382
- Gen Len: 18.9404

## 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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.0338        | 0.23  | 500  | 0.0175          | 0.1514 | 0.0297 | 0.1511 | 0.1518    | 18.9188 |
| 0.0566        | 0.46  | 1000 | 0.0161          | 0.1565 | 0.0388 | 0.157  | 0.1573    | 18.9188 |
| 0.0418        | 0.7   | 1500 | 0.0125          | 0.1372 | 0.0199 | 0.1375 | 0.1379    | 18.8105 |
| 0.0333        | 0.93  | 2000 | 0.0116          | 0.1443 | 0.0253 | 0.1448 | 0.1448    | 18.8051 |
| 0.0287        | 1.16  | 2500 | 0.0110          | 0.144  | 0.0192 | 0.1442 | 0.1442    | 19.0    |
| 0.0247        | 1.39  | 3000 | 0.0096          | 0.1511 | 0.024  | 0.1517 | 0.1518    | 19.0    |
| 0.0219        | 1.62  | 3500 | 0.0087          | 0.1463 | 0.0241 | 0.1462 | 0.1462    | 18.9747 |
| 0.021         | 1.86  | 4000 | 0.0104          | 0.1382 | 0.0187 | 0.1382 | 0.1382    | 18.9404 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2