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---
license: apache-2.0
datasets:
- billsum
tags:
- summarization
- t5
widget:
- text: "The people of the State of California do enact as follows: SECTION 1. The\
\ Legislature hereby finds and declares as follows: (a) Many areas of the state\
\ are disproportionately impacted by drought because they are heavily dependent\
\ or completely reliant on groundwater from basins that are in overdraft and in\
\ which the water table declines year after year or from basins that are contaminated.\
\ (b) There are a number of state grant and loan programs that provide financial\
\ assistance to communities to address drinking water and wastewater needs. Unfortunately,\
\ there is no program in place to provide similar assistance to individual homeowners\
\ who are reliant on their own groundwater wells and who may not be able to afford\
\ conventional private loans to undertake vital water supply, water quality, and\
\ wastewater improvements. (c) The program created by this act is intended to\
\ bridge that gap by providing low-interest loans, grants, or both, to individual\
\ homeowners to undertake actions necessary to provide safer, cleaner, and more\
\ reliable drinking water and wastewater treatment. These actions may include,\
\ but are not limited to, digging deeper wells, improving existing wells and related\
\ equipment, addressing drinking water contaminants in the homeowner\u2019s water,\
\ or connecting to a local water or wastewater system. SEC. 2. Chapter 6.6 (commencing\
\ with Section 13486) is added to Division 7 of the Water Code, to read: CHAPTER\
\ 6.6. Water and Wastewater Loan and Grant Program 13486. (a) The board shall\
\ establish a program in accordance with this chapter to provide low-interest\
\ loans and grants to local agencies for low-interest loans and grants to eligible\
\ applicants for any of the following purposes:"
example_title: Water use
- text: "The people of the State of California do enact as follows: SECTION 1. Section\
\ 2196 of the Elections Code is amended to read: 2196. (a) (1) Notwithstanding\
\ any other provision of law, a person who is qualified to register to vote and\
\ who has a valid California driver\u2019s license or state identification card\
\ may submit an affidavit of voter registration electronically on the Internet\
\ Web site of the Secretary of State. (2) An affidavit submitted pursuant to this\
\ section is effective upon receipt of the affidavit by the Secretary of State\
\ if the affidavit is received on or before the last day to register for an election\
\ to be held in the precinct of the person submitting the affidavit. (3) The affiant\
\ shall affirmatively attest to the truth of the information provided in the affidavit.\
\ (4) For voter registration purposes, the applicant shall affirmatively assent\
\ to the use of his or her signature from his or her driver\u2019s license or\
\ state identification card. (5) For each electronic affidavit, the Secretary\
\ of State shall obtain an electronic copy of the applicant\u2019s signature from\
\ his or her driver\u2019s license or state identification card directly from\
\ the Department of Motor Vehicles. (6) The Secretary of State shall require a\
\ person who submits an affidavit pursuant to this section to submit all of the\
\ following: (A) The number from his or her California driver\u2019s license or\
\ state identification card. (B) His or her date of birth. (C) The last four digits\
\ of his or her social security number. (D) Any other information the Secretary\
\ of State deems necessary to establish the identity of the affiant. (7) Upon\
\ submission of an affidavit pursuant to this section, the electronic voter registration\
\ system shall provide for immediate verification of both of the following:"
example_title: Election
metrics:
- rouge
model-index:
- name: t5-small-finetuned-billsum-ca_test
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
args: default
metrics:
- name: Rouge1
type: rouge
value: 12.6315
- task:
type: summarization
name: Summarization
dataset:
name: billsum
type: billsum
config: default
split: test
metrics:
- name: ROUGE-1
type: rouge
value: 12.1368
verified: true
- name: ROUGE-2
type: rouge
value: 4.6017
verified: true
- name: ROUGE-L
type: rouge
value: 10.0767
verified: true
- name: ROUGE-LSUM
type: rouge
value: 10.6892
verified: true
- name: loss
type: loss
value: 2.897707462310791
verified: true
- name: gen_len
type: gen_len
value: 19.0
verified: true
---
<!-- 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-small-finetuned-billsum-ca_test
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: 2.3376
- Rouge1: 12.6315
- Rouge2: 6.9839
- Rougel: 10.9983
- Rougelsum: 11.9383
- 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 495 | 2.4805 | 9.9389 | 4.1239 | 8.3979 | 9.1599 | 19.0 |
| 3.1564 | 2.0 | 990 | 2.3833 | 12.1026 | 6.5196 | 10.5123 | 11.4527 | 19.0 |
| 2.66 | 3.0 | 1485 | 2.3496 | 12.5389 | 6.8686 | 10.8798 | 11.8636 | 19.0 |
| 2.5671 | 4.0 | 1980 | 2.3376 | 12.6315 | 6.9839 | 10.9983 | 11.9383 | 19.0 |
### Framework versions
- Transformers 4.12.2
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
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