pytorch mt5 text2text-generation dataset:xlsum transformers summarization arabic ar Abstractive Summarization generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- summarization
- arabic
- ar
- mt5
- Abstractive Summarization
- generated_from_trainer
datasets:
- xlsum
model-index:
- name: mt5-base-finetuned-persian-finetuned-persian-arabic
  results: []
---

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# mt5-base-finetuned-persian-finetuned-persian-arabic

This model is a fine-tuned version of [ahmeddbahaa/mt5-base-finetuned-persian](https://huggingface.co/ahmeddbahaa/mt5-base-finetuned-persian) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3234
- Rouge-1: 22.96
- Rouge-2: 10.27
- Rouge-l: 20.95
- Gen Len: 19.0
- Bertscore: 71.59

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 4.2754        | 1.0   | 1172 | 3.5717          | 19.26   | 7.26    | 17.48   | 19.0    | 70.49     |
| 3.7388        | 2.0   | 2344 | 3.4291          | 19.71   | 7.88    | 17.94   | 19.0    | 70.64     |
| 3.541         | 3.0   | 3516 | 3.3653          | 21.18   | 8.84    | 19.35   | 19.0    | 71.05     |
| 3.4113        | 4.0   | 4688 | 3.3306          | 21.54   | 9.11    | 19.65   | 19.0    | 71.19     |
| 3.3256        | 5.0   | 5860 | 3.3234          | 21.69   | 9.22    | 19.81   | 19.0    | 71.31     |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
