---
license: apache-2.0
tags:
- summarization
- persian
- generated_from_trainer
datasets:
- xlsum
model-index:
- name: mt5-base-finetuned-persian
  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-persian

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6086
- Rouge-1: 22.02
- Rouge-2: 7.41
- Rouge-l: 18.95
- Gen Len: 19.0
- Bertscore: 69.89

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
| 7.2823        | 0.96  | 19   | 3.9800          | 19.78   | 5.57    | 16.24   | 19.0    | 68.19     |
| 4.7334        | 1.96  | 38   | 3.7620          | 20.92   | 7.49    | 18.27   | 18.91   | 68.72     |
| 4.3891        | 2.96  | 57   | 3.6349          | 21.07   | 7.66    | 18.53   | 18.96   | 69.73     |
| 4.2           | 3.96  | 76   | 3.6315          | 19.63   | 6.49    | 16.61   | 19.0    | 69.15     |
| 3.9202        | 4.96  | 95   | 3.6086          | 21.2    | 6.8     | 17.06   | 19.0    | 69.48     |


### Framework versions

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