---
license: mit
base_model: KingLTD/pretrain_Law_model_vit5_version2
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pretrain_Law_model_vit5_version3
  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_version3

This model is a fine-tuned version of [KingLTD/pretrain_Law_model_vit5_version2](https://huggingface.co/KingLTD/pretrain_Law_model_vit5_version2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1136
- Rouge1: 0.4973
- Rouge2: 0.4075
- Rougel: 0.4532
- Rougelsum: 0.4674

## 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  | 0.1060          | 0.4960 | 0.4069 | 0.4502 | 0.4664    |
| No log        | 2.0   | 490  | 0.1070          | 0.4946 | 0.4053 | 0.4484 | 0.4644    |
| 0.146         | 3.0   | 735  | 0.1079          | 0.4908 | 0.3988 | 0.4456 | 0.4601    |
| 0.146         | 4.0   | 980  | 0.1107          | 0.4994 | 0.4094 | 0.4508 | 0.4665    |
| 0.1149        | 5.0   | 1225 | 0.1107          | 0.4944 | 0.4024 | 0.4483 | 0.4635    |
| 0.1149        | 6.0   | 1470 | 0.1126          | 0.4931 | 0.4028 | 0.4478 | 0.4626    |
| 0.0956        | 7.0   | 1715 | 0.1124          | 0.4991 | 0.4108 | 0.4556 | 0.4701    |
| 0.0956        | 8.0   | 1960 | 0.1122          | 0.4944 | 0.4082 | 0.4515 | 0.4655    |
| 0.0822        | 9.0   | 2205 | 0.1133          | 0.4996 | 0.4111 | 0.4557 | 0.4699    |
| 0.0822        | 10.0  | 2450 | 0.1136          | 0.4973 | 0.4075 | 0.4532 | 0.4674    |


### Framework versions

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