---
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: 1.9529
- Rouge1: 46.9407
- Rouge2: 20.9876
- Rougel: 33.0832
- Rougelsum: 33.2396
- Gen Len: 18.9604

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.2864        | 1.0   | 2007 | 1.9529          | 46.9407 | 20.9876 | 33.0832 | 33.2396   | 18.9604 |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.13.3