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---
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: 0.2349
- Bleu Score: 79.18
- Precision: 56.1529
- Recall: 56.1529
- Gen Len: 12.7933
- Err: 56.1529
## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
| 0.4686 | 1.0 | 838 | 0.2500 | 77.4389 | 50.1792 | 50.1792 | 12.8244 | 50.1792 |
| 0.1722 | 2.0 | 1676 | 0.2120 | 78.5311 | 54.1219 | 54.1219 | 12.7933 | 54.1219 |
| 0.0703 | 3.0 | 2514 | 0.2349 | 79.18 | 56.1529 | 56.1529 | 12.7933 | 56.1529 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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