---
tags:
- summarization
- ar
- Abstractive Summarization
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: AraT5-base-finetune-ar-wikilingua
  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. -->

# AraT5-base-finetune-ar-wikilingua

This model is a fine-tuned version of [UBC-NLP/AraT5-base](https://huggingface.co/UBC-NLP/AraT5-base) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6110
- Rouge-1: 19.97
- Rouge-2: 6.9
- Rouge-l: 18.25
- Gen Len: 18.45
- Bertscore: 69.44

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 10
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 11.5412       | 1.0   | 312  | 6.8825          | 5.2     | 0.69    | 5.04    | 19.0    | 63.2      |
| 6.5212        | 2.0   | 624  | 5.8992          | 8.89    | 1.4     | 8.36    | 17.92   | 63.9      |
| 5.8302        | 3.0   | 936  | 5.3712          | 9.99    | 2.21    | 9.54    | 15.87   | 65.08     |
| 5.406         | 4.0   | 1248 | 5.0632          | 13.94   | 3.5     | 13.0    | 15.95   | 66.83     |
| 5.1109        | 5.0   | 1560 | 4.8718          | 15.28   | 4.34    | 14.27   | 18.26   | 66.83     |
| 4.9004        | 6.0   | 1872 | 4.7631          | 16.65   | 4.92    | 15.46   | 17.73   | 67.75     |
| 4.754         | 7.0   | 2184 | 4.6920          | 18.31   | 5.79    | 16.9    | 18.17   | 68.55     |
| 4.6369        | 8.0   | 2496 | 4.6459          | 18.6    | 6.12    | 17.16   | 18.16   | 68.66     |
| 4.5595        | 9.0   | 2808 | 4.6153          | 18.94   | 6.1     | 17.39   | 17.82   | 68.99     |
| 4.4967        | 10.0  | 3120 | 4.6110          | 19.15   | 6.25    | 17.55   | 17.91   | 69.09     |


### Framework versions

- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1