---
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: 0.2324
- Bleu Score: 79.5557
- Precision: 100.0
- Recall: 93.3333
- Gen Len: 12.7969
- Err: 56.9892

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall  | Gen Len | Err     |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
| 0.4672        | 1.0   | 419  | 0.2390          | 76.7871    | 100.0     | 100.0   | 12.8292 | 49.7013 |
| 0.1742        | 2.0   | 838  | 0.2173          | 77.9698    | 100.0     | 93.3333 | 12.8076 | 54.0024 |
| 0.0814        | 3.0   | 1257 | 0.2010          | 79.204     | 100.0     | 93.3333 | 12.7754 | 56.6308 |
| 0.0382        | 4.0   | 1676 | 0.2324          | 79.5557    | 100.0     | 93.3333 | 12.7969 | 56.9892 |


### Framework versions

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