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--- |
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license: apache-2.0 |
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datasets: |
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- billsum |
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tags: |
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- summarization |
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- t5 |
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widget: |
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- text: "The people of the State of California do enact as follows: SECTION 1. The\ |
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\ Legislature hereby finds and declares as follows: (a) Many areas of the state\ |
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\ are disproportionately impacted by drought because they are heavily dependent\ |
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\ or completely reliant on groundwater from basins that are in overdraft and in\ |
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\ which the water table declines year after year or from basins that are contaminated.\ |
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\ (b) There are a number of state grant and loan programs that provide financial\ |
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\ assistance to communities to address drinking water and wastewater needs. Unfortunately,\ |
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\ there is no program in place to provide similar assistance to individual homeowners\ |
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\ who are reliant on their own groundwater wells and who may not be able to afford\ |
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\ conventional private loans to undertake vital water supply, water quality, and\ |
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\ wastewater improvements. (c) The program created by this act is intended to\ |
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\ bridge that gap by providing low-interest loans, grants, or both, to individual\ |
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\ homeowners to undertake actions necessary to provide safer, cleaner, and more\ |
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\ reliable drinking water and wastewater treatment. These actions may include,\ |
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\ but are not limited to, digging deeper wells, improving existing wells and related\ |
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\ equipment, addressing drinking water contaminants in the homeowner\u2019s water,\ |
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\ or connecting to a local water or wastewater system. SEC. 2. Chapter 6.6 (commencing\ |
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\ with Section 13486) is added to Division 7 of the Water Code, to read: CHAPTER\ |
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\ 6.6. Water and Wastewater Loan and Grant Program 13486. (a) The board shall\ |
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\ establish a program in accordance with this chapter to provide low-interest\ |
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\ loans and grants to local agencies for low-interest loans and grants to eligible\ |
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\ applicants for any of the following purposes:" |
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example_title: Water use |
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- text: "The people of the State of California do enact as follows: SECTION 1. Section\ |
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\ 2196 of the Elections Code is amended to read: 2196. (a) (1) Notwithstanding\ |
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\ any other provision of law, a person who is qualified to register to vote and\ |
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\ who has a valid California driver\u2019s license or state identification card\ |
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\ may submit an affidavit of voter registration electronically on the Internet\ |
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\ Web site of the Secretary of State. (2) An affidavit submitted pursuant to this\ |
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\ section is effective upon receipt of the affidavit by the Secretary of State\ |
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\ if the affidavit is received on or before the last day to register for an election\ |
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\ to be held in the precinct of the person submitting the affidavit. (3) The affiant\ |
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\ shall affirmatively attest to the truth of the information provided in the affidavit.\ |
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\ (4) For voter registration purposes, the applicant shall affirmatively assent\ |
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\ to the use of his or her signature from his or her driver\u2019s license or\ |
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\ state identification card. (5) For each electronic affidavit, the Secretary\ |
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\ of State shall obtain an electronic copy of the applicant\u2019s signature from\ |
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\ his or her driver\u2019s license or state identification card directly from\ |
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\ the Department of Motor Vehicles. (6) The Secretary of State shall require a\ |
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\ person who submits an affidavit pursuant to this section to submit all of the\ |
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\ following: (A) The number from his or her California driver\u2019s license or\ |
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\ state identification card. (B) His or her date of birth. (C) The last four digits\ |
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\ of his or her social security number. (D) Any other information the Secretary\ |
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\ of State deems necessary to establish the identity of the affiant. (7) Upon\ |
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\ submission of an affidavit pursuant to this section, the electronic voter registration\ |
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\ system shall provide for immediate verification of both of the following:" |
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example_title: Election |
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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-billsum-ca_test |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: billsum |
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type: billsum |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 12.6315 |
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- task: |
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type: summarization |
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name: Summarization |
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dataset: |
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name: billsum |
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type: billsum |
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config: default |
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split: test |
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metrics: |
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- name: ROUGE-1 |
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type: rouge |
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value: 12.1368 |
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verified: true |
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- name: ROUGE-2 |
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type: rouge |
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value: 4.6017 |
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verified: true |
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- name: ROUGE-L |
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type: rouge |
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value: 10.0767 |
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verified: true |
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- name: ROUGE-LSUM |
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type: rouge |
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value: 10.6892 |
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verified: true |
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- name: loss |
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type: loss |
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value: 2.897707462310791 |
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verified: true |
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- name: gen_len |
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type: gen_len |
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value: 19.0 |
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verified: true |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# t5-small-finetuned-billsum-ca_test |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3376 |
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- Rouge1: 12.6315 |
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- Rouge2: 6.9839 |
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- Rougel: 10.9983 |
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- Rougelsum: 11.9383 |
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- Gen Len: 19.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| |
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| No log | 1.0 | 495 | 2.4805 | 9.9389 | 4.1239 | 8.3979 | 9.1599 | 19.0 | |
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| 3.1564 | 2.0 | 990 | 2.3833 | 12.1026 | 6.5196 | 10.5123 | 11.4527 | 19.0 | |
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| 2.66 | 3.0 | 1485 | 2.3496 | 12.5389 | 6.8686 | 10.8798 | 11.8636 | 19.0 | |
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| 2.5671 | 4.0 | 1980 | 2.3376 | 12.6315 | 6.9839 | 10.9983 | 11.9383 | 19.0 | |
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### Framework versions |
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- Transformers 4.12.2 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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