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---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: 3_loa
results: []
library_name: peft
---
<!-- 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
- PEFT 0.4.0
- Transformers 4.31.0
- Pytorch 1.13.1.post200
- Datasets 2.10.0
- Tokenizers 0.13.2
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