---
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: 1.8974
- Rouge1: 46.8897
- Rouge2: 21.2655
- Rougel: 33.489
- Rougelsum: 33.5578
- Gen Len: 18.9871

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.408         | 1.0   | 737  | 1.9329          | 46.6812 | 20.8232 | 33.1637 | 33.2377   | 18.9608 |
| 2.0444        | 2.0   | 1475 | 1.8841          | 46.7693 | 21.3121 | 33.37   | 33.4394   | 18.9623 |
| 1.7589        | 3.0   | 2212 | 1.8840          | 46.6303 | 21.0522 | 33.2678 | 33.3244   | 18.9777 |
| 1.6919        | 4.0   | 2950 | 1.8864          | 46.7928 | 21.395  | 33.3749 | 33.4439   | 18.9911 |
| 1.5844        | 5.0   | 3685 | 1.8974          | 46.8897 | 21.2655 | 33.489  | 33.5578   | 18.9871 |


### Framework versions

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