---
license: mit
base_model: KingLTD/pretrain_Law_model_vit5_version1
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pretrain_Law_model_vit5_version2
  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_version2

This model is a fine-tuned version of [KingLTD/pretrain_Law_model_vit5_version1](https://huggingface.co/KingLTD/pretrain_Law_model_vit5_version1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1644
- Rouge1: 0.4902
- Rouge2: 0.3828
- Rougel: 0.4363
- Rougelsum: 0.4521

## 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  | 0.1692          | 0.4844 | 0.3722 | 0.4279 | 0.4439    |
| No log        | 2.0   | 490  | 0.1664          | 0.4846 | 0.3719 | 0.4261 | 0.4442    |
| 0.2198        | 3.0   | 735  | 0.1636          | 0.4840 | 0.3752 | 0.4292 | 0.4443    |
| 0.2198        | 4.0   | 980  | 0.1628          | 0.4878 | 0.3754 | 0.4300 | 0.4468    |
| 0.178         | 5.0   | 1225 | 0.1621          | 0.4871 | 0.3791 | 0.4349 | 0.4494    |
| 0.178         | 6.0   | 1470 | 0.1625          | 0.4881 | 0.3782 | 0.4328 | 0.4495    |
| 0.1466        | 7.0   | 1715 | 0.1636          | 0.4910 | 0.3837 | 0.4383 | 0.4538    |
| 0.1466        | 8.0   | 1960 | 0.1633          | 0.4890 | 0.3802 | 0.4343 | 0.4506    |
| 0.1307        | 9.0   | 2205 | 0.1642          | 0.4904 | 0.3836 | 0.4364 | 0.4531    |
| 0.1307        | 10.0  | 2450 | 0.1644          | 0.4902 | 0.3828 | 0.4363 | 0.4521    |


### Framework versions

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