---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: vit5-base-vietnews-summarization-finetuned-VN
  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. -->

# vit5-base-vietnews-summarization-finetuned-VN

This model is a fine-tuned version of [VietAI/vit5-base-vietnews-summarization](https://huggingface.co/VietAI/vit5-base-vietnews-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9536
- Rouge1: 47.0452
- Rouge2: 21.1233
- Rougel: 33.2693
- Rougelsum: 33.4168
- Gen Len: 18.9626

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.3275        | 1.0   | 1982 | 1.9536          | 47.0452 | 21.1233 | 33.2693 | 33.4168   | 18.9626 |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.13.3