---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: 3_loa
  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. -->

# 3_loa

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5159
- Rouge1: 0.2005
- Rouge2: 0.1122
- Rougel: 0.1739
- Rougelsum: 0.1738
- Gen Len: 19.0

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.0741        | 1.0   | 989   | 1.7085          | 0.2064 | 0.1145 | 0.1771 | 0.1771    | 19.0    |
| 1.8521        | 2.0   | 1978  | 1.6510          | 0.2021 | 0.109  | 0.1744 | 0.1743    | 19.0    |
| 1.7753        | 3.0   | 2967  | 1.6182          | 0.2015 | 0.1099 | 0.1742 | 0.1742    | 19.0    |
| 1.7481        | 4.0   | 3956  | 1.5940          | 0.1995 | 0.1102 | 0.1736 | 0.1737    | 19.0    |
| 1.6966        | 5.0   | 4945  | 1.5771          | 0.1999 | 0.1112 | 0.1739 | 0.1738    | 19.0    |
| 1.7107        | 6.0   | 5934  | 1.5629          | 0.1974 | 0.1091 | 0.1721 | 0.1721    | 19.0    |
| 1.6905        | 7.0   | 6923  | 1.5527          | 0.1993 | 0.1091 | 0.1737 | 0.1737    | 19.0    |
| 1.6341        | 8.0   | 7912  | 1.5475          | 0.1994 | 0.11   | 0.1732 | 0.1731    | 19.0    |
| 1.6649        | 9.0   | 8901  | 1.5422          | 0.1978 | 0.109  | 0.1726 | 0.1722    | 19.0    |
| 1.6338        | 10.0  | 9890  | 1.5339          | 0.2009 | 0.1125 | 0.1748 | 0.1744    | 19.0    |
| 1.6545        | 11.0  | 10879 | 1.5310          | 0.201  | 0.1138 | 0.1759 | 0.1757    | 19.0    |
| 1.6617        | 12.0  | 11868 | 1.5323          | 0.2026 | 0.1152 | 0.1762 | 0.1761    | 19.0    |
| 1.629         | 13.0  | 12857 | 1.5245          | 0.202  | 0.1143 | 0.1752 | 0.1751    | 19.0    |
| 1.6202        | 14.0  | 13846 | 1.5214          | 0.2021 | 0.1138 | 0.1752 | 0.1751    | 19.0    |
| 1.6127        | 15.0  | 14835 | 1.5206          | 0.2013 | 0.113  | 0.1746 | 0.1743    | 19.0    |
| 1.6072        | 16.0  | 15824 | 1.5171          | 0.1991 | 0.1112 | 0.1731 | 0.1727    | 19.0    |
| 1.6032        | 17.0  | 16813 | 1.5180          | 0.1997 | 0.1126 | 0.1737 | 0.1735    | 19.0    |
| 1.6103        | 18.0  | 17802 | 1.5169          | 0.1999 | 0.1128 | 0.1741 | 0.1738    | 19.0    |
| 1.5956        | 19.0  | 18791 | 1.5160          | 0.2008 | 0.1128 | 0.1743 | 0.174     | 19.0    |
| 1.5981        | 20.0  | 19780 | 1.5159          | 0.2005 | 0.1122 | 0.1739 | 0.1738    | 19.0    |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.13.1.post200
- Datasets 2.10.0
- Tokenizers 0.13.2