---
library_name: transformers
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: ViNormT5
  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. -->

# ViNormT5

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2178
- Bleu Score: 78.7261
- Precision: 54.5998
- Recall: 54.5998
- Gen Len: 12.7826
- Err: 54.5998

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall  | Gen Len | Err     |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
| 0.4635        | 1.0   | 419  | 0.2255          | 77.2678    | 49.5818   | 49.5818 | 12.7969 | 49.5818 |
| 0.166         | 2.0   | 838  | 0.2026          | 78.2851    | 53.1661   | 53.1661 | 12.8041 | 53.1661 |
| 0.0752        | 3.0   | 1257 | 0.2178          | 78.7261    | 54.5998   | 54.5998 | 12.7826 | 54.5998 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0