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---
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
|