---
base_model: csebuetnlp/mT5_multilingual_XLSum
tags:
- summary
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9889
- Rouge1: 37.6658
- Rouge2: 25.8954
- Rougel: 30.7965
- Rougelsum: 30.7895

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.8494        | 0.9888 | 55   | 2.2040          | 35.3021 | 24.7331 | 29.5323 | 29.5469   |
| 2.3422        | 1.9955 | 111  | 2.0275          | 37.3011 | 25.7964 | 30.7416 | 30.7363   |
| 2.2332        | 2.9663 | 165  | 1.9889          | 37.6658 | 25.8954 | 30.7965 | 30.7895   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1