---
license: apache-2.0
tags:
- summarization
- arabic
- ar
- mt5
- Abstractive Summarization
- generated_from_trainer
datasets:
- xlsum
model-index:
- name: mt5-base-finetuned-urdu-finetuned-urdu-arabic
  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-base-finetuned-urdu-finetuned-urdu-arabic

This model is a fine-tuned version of [eslamxm/mt5-base-finetuned-urdu](https://huggingface.co/eslamxm/mt5-base-finetuned-urdu) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3744
- Rouge-1: 22.77
- Rouge-2: 10.15
- Rouge-l: 20.71
- Gen Len: 19.0
- Bertscore: 71.46

## 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: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 4.5155        | 1.0   | 1172 | 3.6895          | 18.81   | 6.77    | 17.01   | 19.0    | 70.27     |
| 3.8315        | 2.0   | 2344 | 3.5047          | 19.75   | 7.79    | 17.95   | 19.0    | 70.58     |
| 3.6122        | 3.0   | 3516 | 3.4231          | 20.46   | 8.44    | 18.7    | 19.0    | 70.8      |
| 3.4735        | 4.0   | 4688 | 3.3835          | 21.12   | 8.86    | 19.21   | 19.0    | 70.98     |
| 3.3855        | 5.0   | 5860 | 3.3744          | 21.48   | 9.01    | 19.57   | 19.0    | 71.17     |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1