---
license: mit
base_model: VietAI/vit5-base-vietnews-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: vit5-base-vietnews-summarization-sport
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit5-base-vietnews-summarization-sport

This model is a fine-tuned version of [VietAI/vit5-base-vietnews-summarization](https://huggingface.co/VietAI/vit5-base-vietnews-summarization) on an toanduc/vietnamese-sport-newspapers-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7541
- Rouge1: 24.4342
- Rouge2: 12.2779
- Rougel: 18.7382
- Rougelsum: 21.4735
- Gen Len: 19.0

## Model description

Summary model for Vietnamese sports articles under the transfer tag

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.7931        | 1.0   | 2897  | 1.6246          | 25.1902 | 11.9842 | 18.7125 | 21.8765   | 19.0    |
| 1.5869        | 2.0   | 5794  | 1.5557          | 24.8104 | 12.918  | 19.1867 | 21.9091   | 19.0    |
| 1.4568        | 3.0   | 8691  | 1.5264          | 24.3498 | 12.6452 | 18.7426 | 21.4748   | 19.0    |
| 1.3375        | 4.0   | 11588 | 1.5259          | 24.3584 | 12.2843 | 18.7177 | 21.4296   | 19.0    |
| 1.2417        | 5.0   | 14485 | 1.5299          | 24.3633 | 11.9901 | 18.5573 | 21.4541   | 19.0    |
| 1.1705        | 6.0   | 17382 | 1.5533          | 24.4314 | 12.3337 | 18.7517 | 21.5669   | 19.0    |
| 1.0965        | 7.0   | 20279 | 1.5716          | 24.7562 | 12.4883 | 18.8926 | 21.7281   | 19.0    |
| 1.0479        | 8.0   | 23176 | 1.5918          | 24.3464 | 12.4018 | 18.6725 | 21.3891   | 19.0    |
| 0.9993        | 9.0   | 26073 | 1.6116          | 24.6254 | 12.1213 | 18.7091 | 21.5747   | 19.0    |
| 0.9512        | 10.0  | 28970 | 1.6427          | 24.6133 | 12.4088 | 18.8244 | 21.6162   | 19.0    |
| 0.8903        | 11.0  | 31867 | 1.6595          | 24.4154 | 12.4455 | 18.721  | 21.4605   | 19.0    |
| 0.8463        | 12.0  | 34764 | 1.6953          | 24.6333 | 12.2631 | 18.8074 | 21.6077   | 19.0    |
| 0.8224        | 13.0  | 37661 | 1.7127          | 24.2227 | 12.141  | 18.5775 | 21.321    | 19.0    |
| 0.8003        | 14.0  | 40558 | 1.7348          | 24.3755 | 12.1357 | 18.6279 | 21.383    | 19.0    |
| 0.7771        | 15.0  | 43455 | 1.7455          | 24.4422 | 12.1864 | 18.7155 | 21.4499   | 19.0    |
| 0.7666        | 16.0  | 46352 | 1.7541          | 24.4342 | 12.2779 | 18.7382 | 21.4735   | 19.0    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2