---
license: mit
base_model: VietAI/vit5-large-vietnews-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: finetuned-news_summarization_vi
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/minhquy16/huggingface/runs/4usld66u)
# finetuned-news_summarization_vi

This model is a fine-tuned version of [VietAI/vit5-large-vietnews-summarization](https://huggingface.co/VietAI/vit5-large-vietnews-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2271
- Rouge1: 0.253
- Rouge2: 0.1919
- Rougel: 0.2233
- Rougelsum: 0.2233
- Gen Len: 18.496

## 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: 1
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.2561        | 1.0   | 65361  | 0.2342          | 0.248  | 0.1883 | 0.2192 | 0.2192    | 18.274  |
| 0.1831        | 2.0   | 130722 | 0.2271          | 0.253  | 0.1919 | 0.2233 | 0.2233    | 18.496  |


### Framework versions

- Transformers 4.43.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1