---
base_model: UBC-NLP/AraT5v2-base-1024
tags:
- summarization
- Arat5v2
- abstractive summarization
- ar
- wikilingua
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: AraT5v2-base-1024-finetuned-ar-wikilingua
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# AraT5v2-base-1024-finetuned-ar-wikilingua

This model is a fine-tuned version of [UBC-NLP/AraT5v2-base-1024](https://huggingface.co/UBC-NLP/AraT5v2-base-1024) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1591
- Rouge-1: 26.54
- Rouge-2: 10.4
- Rouge-l: 23.72
- Gen Len: 18.19
- Bertscore: 72.52

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 8
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 5.2884        | 1.0   | 4998  | 4.4307          | 23.0    | 8.16    | 20.56   | 17.66   | 70.77     |
| 4.6798        | 2.0   | 9996  | 4.2972          | 24.48   | 8.95    | 21.86   | 17.57   | 71.56     |
| 4.4355        | 3.0   | 14994 | 4.2313          | 24.85   | 9.17    | 22.23   | 17.68   | 71.7      |
| 4.2772        | 4.0   | 19992 | 4.1972          | 25.41   | 9.5     | 22.65   | 17.63   | 72.08     |
| 4.1551        | 5.0   | 24990 | 4.1724          | 25.43   | 9.44    | 22.58   | 17.68   | 72.08     |
| 4.0604        | 6.0   | 29988 | 4.1626          | 25.44   | 9.56    | 22.67   | 17.52   | 72.19     |
| 3.989         | 7.0   | 34986 | 4.1616          | 25.71   | 9.68    | 22.91   | 17.71   | 72.29     |
| 3.9467        | 8.0   | 39984 | 4.1591          | 25.81   | 9.81    | 23.03   | 17.67   | 72.33     |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3