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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: T5_summ_gen_v1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
config: default
split: ca_test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.1986
---
<!-- 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. -->
# T5_summ_gen_v1
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0950
- Rouge1: 0.1986
- Rouge2: 0.1044
- Rougel: 0.1726
- Rougelsum: 0.1727
- 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 62 | 2.2294 | 0.1988 | 0.1023 | 0.1715 | 0.1714 | 19.0 |
| No log | 2.0 | 124 | 2.2038 | 0.1998 | 0.1024 | 0.1727 | 0.1725 | 19.0 |
| No log | 3.0 | 186 | 2.1890 | 0.2011 | 0.1049 | 0.1744 | 0.1746 | 19.0 |
| No log | 4.0 | 248 | 2.1767 | 0.2002 | 0.1059 | 0.1736 | 0.1737 | 19.0 |
| No log | 5.0 | 310 | 2.1593 | 0.2015 | 0.1064 | 0.1739 | 0.1741 | 19.0 |
| No log | 6.0 | 372 | 2.1522 | 0.2022 | 0.1059 | 0.1747 | 0.175 | 19.0 |
| No log | 7.0 | 434 | 2.1404 | 0.2028 | 0.1078 | 0.1746 | 0.1748 | 19.0 |
| No log | 8.0 | 496 | 2.1369 | 0.2015 | 0.1061 | 0.1735 | 0.1737 | 19.0 |
| 2.382 | 9.0 | 558 | 2.1299 | 0.1999 | 0.1053 | 0.1723 | 0.1725 | 19.0 |
| 2.382 | 10.0 | 620 | 2.1205 | 0.2003 | 0.1058 | 0.173 | 0.1729 | 19.0 |
| 2.382 | 11.0 | 682 | 2.1170 | 0.1998 | 0.105 | 0.1727 | 0.1727 | 19.0 |
| 2.382 | 12.0 | 744 | 2.1122 | 0.2003 | 0.1057 | 0.1734 | 0.1734 | 19.0 |
| 2.382 | 13.0 | 806 | 2.1084 | 0.1993 | 0.1042 | 0.1725 | 0.1726 | 19.0 |
| 2.382 | 14.0 | 868 | 2.1046 | 0.1988 | 0.1037 | 0.1723 | 0.1725 | 19.0 |
| 2.382 | 15.0 | 930 | 2.1023 | 0.1992 | 0.1047 | 0.1727 | 0.1729 | 19.0 |
| 2.382 | 16.0 | 992 | 2.1006 | 0.1992 | 0.1047 | 0.1727 | 0.1729 | 19.0 |
| 2.2855 | 17.0 | 1054 | 2.0979 | 0.1983 | 0.1034 | 0.1722 | 0.1723 | 19.0 |
| 2.2855 | 18.0 | 1116 | 2.0961 | 0.1988 | 0.1046 | 0.1729 | 0.173 | 19.0 |
| 2.2855 | 19.0 | 1178 | 2.0953 | 0.1986 | 0.1044 | 0.1725 | 0.1726 | 19.0 |
| 2.2855 | 20.0 | 1240 | 2.0950 | 0.1986 | 0.1044 | 0.1726 | 0.1727 | 19.0 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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