---
tags:
- summarization
- generated_from_trainer
datasets:
- wiki_lingua
model-index:
- name: mT5_multilingual_XLSum-finetuned-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. -->

# mT5_multilingual_XLSum-finetuned-ar-wikilingua

This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6903
- Rouge-1: 24.47
- Rouge-2: 7.69
- Rouge-l: 20.04
- Gen Len: 39.64
- Bertscore: 72.63

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 4.4406        | 1.0   | 5111  | 3.9582          | 22.35   | 6.84    | 18.39   | 34.78   | 71.94     |
| 4.0158        | 2.0   | 10222 | 3.8316          | 22.87   | 7.24    | 18.92   | 34.7    | 71.99     |
| 3.8626        | 3.0   | 15333 | 3.7695          | 23.65   | 7.5     | 19.6    | 35.53   | 72.31     |
| 3.7626        | 4.0   | 20444 | 3.7313          | 24.01   | 7.59    | 19.68   | 38.16   | 72.41     |
| 3.6934        | 5.0   | 25555 | 3.7118          | 24.37   | 7.77    | 19.93   | 39.36   | 72.47     |
| 3.6421        | 6.0   | 30666 | 3.7016          | 24.48   | 7.8     | 20.07   | 38.58   | 72.58     |
| 3.6073        | 7.0   | 35777 | 3.6907          | 24.31   | 7.83    | 20.13   | 38.07   | 72.5      |
| 3.5843        | 8.0   | 40888 | 3.6903          | 24.55   | 7.88    | 20.2    | 38.33   | 72.6      |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1