---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pretrain_Law_model_vit5_version1
  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. -->

# pretrain_Law_model_vit5_version1

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2779
- Rouge1: 0.4859
- Rouge2: 0.3617
- Rougel: 0.4218
- Rougelsum: 0.4417

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 245  | 0.3566          | 0.4739 | 0.3369 | 0.4053 | 0.4273    |
| No log        | 2.0   | 490  | 0.3240          | 0.4752 | 0.3453 | 0.4095 | 0.4300    |
| 0.7518        | 3.0   | 735  | 0.3059          | 0.4760 | 0.3510 | 0.4112 | 0.4311    |
| 0.7518        | 4.0   | 980  | 0.2951          | 0.4838 | 0.3584 | 0.4164 | 0.4387    |
| 0.2808        | 5.0   | 1225 | 0.2858          | 0.4799 | 0.3582 | 0.4166 | 0.4368    |
| 0.2808        | 6.0   | 1470 | 0.2831          | 0.4839 | 0.3611 | 0.4194 | 0.4403    |
| 0.2351        | 7.0   | 1715 | 0.2814          | 0.4858 | 0.3644 | 0.4218 | 0.4423    |
| 0.2351        | 8.0   | 1960 | 0.2779          | 0.4850 | 0.3612 | 0.4206 | 0.4416    |
| 0.2074        | 9.0   | 2205 | 0.2775          | 0.4836 | 0.3590 | 0.4199 | 0.4398    |
| 0.2074        | 10.0  | 2450 | 0.2779          | 0.4859 | 0.3617 | 0.4218 | 0.4417    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3