---
license: mit
base_model: VietAI/vit5-base-vietnews-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_summarize_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. -->

# my_summarize_vi

This model is a fine-tuned version of [VietAI/vit5-base-vietnews-summarization](https://huggingface.co/VietAI/vit5-base-vietnews-summarization) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7072
- Rouge1: 0.2541
- Rouge2: 0.1945
- Rougel: 0.2328
- Rougelsum: 0.233
- Gen Len: 19.0

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.0682        | 1.0   | 801  | 0.6850          | 0.252  | 0.1922 | 0.2305 | 0.2304    | 19.0    |
| 0.7129        | 2.0   | 1602 | 0.6764          | 0.2515 | 0.1862 | 0.2273 | 0.2274    | 19.0    |
| 0.5657        | 3.0   | 2403 | 0.6899          | 0.2553 | 0.1959 | 0.2334 | 0.2335    | 19.0    |
| 0.4963        | 4.0   | 3204 | 0.7072          | 0.2541 | 0.1945 | 0.2328 | 0.233     | 19.0    |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3