metadata

language:
  - en
tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:53224
  - loss:MultipleNegativesRankingLoss
base_model: sentence-transformers/all-mpnet-base-v2
widget:
  - source_sentence: ' A juridical person may not be a partner of a civil law union. '
    sentences:
      - >

        Article 34

        An not-for-profit association or foundation that is involved in academic
        activities, art, charity, worship, religion, or any other matter of
        public interest may be established as a juridical person with the
        permission of the competent government agency..
      - >

        Article 192

        A person that commences the possession of movables peacefully and openly
        by a transactional act acquires the rights that are exercised with
        respect to the movables immediately if the person possesses it in good
        faith and without negligence..
      - >

        Article 550

        Gifts not in writing may be cancelled by either party;provided, however,
        that this does not apply to a portion of the gift for which performance
        has been completed..
  - source_sentence: >-
      are there any legal systems in the world where the judiciary and the
      legislature are the same? it's well known that the limited lawmaking power
      that a judiciary has comes from interpretation of statutes but are there
      any systems where the judiciary and the legislature are one and the same
      and have broad lawmaking powers ?
    sentences:
      - >-
        Short Answer Is it illegal for US citizens to travel to North Korea? Yes
        (but see the &quot;fine print&quot; below). Long Answer There is: a US
        travel ban to North Korea for American citizens, as of July 2017. Now,
        Americans wishing to travel to North Korea must obtain a Special
        Validation Passport from the US Department of State, only issued under
        very specific circumstances, such as for journalists covering the region
        or for humanitarian aid workers. The Biden administration extended the
        ban, initially established by the Trump administration, on traveling to
        North Korea on a U.S. passport absent special approval: The ban makes it
        illegal to use a U.S. passport for travel to, from or through North
        Korea, also known as the Democratic People's Republic of Korea, or the
        DPRK, unless the document has been specially validated. Such validations
        are granted by the State Department only in the case of compelling
        national interest. The U.S. State Department confirms that this ban is
        still in place. It states that: Travel to, in, or through North Korea on
        a U.S. passport without this special validation may justify revocation
        of your passport for misuse under 22 C.F.R. § 51.62(a)(3) and may
        subject you to felony prosecution under 18 U.S.C. § 1544 or other
        applicable laws. The maximum criminal penalty if you use a U.S. passport
        to go to North Korea and then return and a charged with a crime under 18
        U.S.C. § 1544 are quite serious. You could be sent to prison for up to
        ten years for a first or second offense, or up to fifteen years if you
        have two prior convictions under this statute, and/or fined, even if you
        weren't a terrorist or drug dealer, although the actual sentence would
        probably be milder, if you were charged with a crime at all. The
        criminal statute reads as follows (with the pertinent parts in bold):
        Whoever willfully and knowingly uses, or attempts to use, any passport
        issued or designed for the use of another; or Whoever willfully and
        knowingly uses or attempts to use any passport in violation of the
        conditions or restrictions therein contained, or of the rules prescribed
        pursuant to the laws regulating the issuance of passports; or Whoever
        willfully and knowingly furnishes, disposes of, or delivers a passport
        to any person, for use by another than the person for whose use it was
        originally issued and designed— Shall be fined under this title,
        imprisoned not more than 25 years (if the offense was committed to
        facilitate an act of international terrorism (as defined in section 2331
        of this title)), 20 years (if the offense was committed to facilitate a
        drug trafficking crime (as defined in section 929(a) of this title)), 10
        years (in the case of the first or second such offense, if the offense
        was not committed to facilitate such an act of international terrorism
        or a drug trafficking crime), or 15 years (in the case of any other
        offense), or both. There are also many other North Korean sanctions (and
        keep in mind that North Korea is legally an &quot;enemy&quot; of the
        United States with which the U.S. is officially still at war and does
        not have diplomatic relations). The most recent of those, from 2017,
        prohibits ships and aircraft owned by a &quot;foreign person&quot; which
        have been in North Korean in the last 180 days from entering the United
        States. The ban does not prohibit a dual citizen from traveling to North
        Korea on a passport from the person's other country of citizenship, nor
        does it prohibit U.S. citizens from entering North Korea without using a
        passport (although entering North Korea without a passport or visa
        probably violates North Korean law). Of course, North Korea also
        regulates entry of people into North Korea under North Korean
        immigration laws. I do not know whether or not it is legal under North
        Korean law for people to enter it with a U.S. passport. But, given that
        the only U.S. citizen to enter North Korea without a special U.S. visa
        authorizing the trip in the last seven years was arrested immediately
        after crossing into North Korea this week, it would appear that this is
        illegal under North Korean law as well.
      - >-
        Historically, this was true in the Icelandic Commonwealth in the Middle
        Ages, and in some democratic Greek city-states in the classical era.
        Similarly, in non-democratic feudal regimes, the lord or monarch was
        both the law giver and sitting in court was also the arbiter of all
        disputes arising under the lord's own laws. In places like Saudi Arabia
        where the monarchy's power is more than symbolic, the system still works
        this way to a significant extent. The practical reality in most one
        party Communist states is similar. In the United Kingdom, historically,
        the Appellate committee of the House of Lords (staffed by a subset of
        aristocrats usually appointed for life by the Prime Minister to the
        post) was the highest court of appeal of other courts in the British
        Commonwealth (with the Judicial committee of the Privy Council handling
        final appeals from outside Britain), and it was also a court of original
        jurisdiction for certain criminal cases against other aristocrats to
        satisfy the Magna Carta's notion that one is entitled to a jury of one's
        peers. Top level general purpose legislatures rarely serve as courts at
        the highest level, except in very isolated political matters. A good
        example of narrow quasi-judicial legislative power is the power of the
        Congress in the U.S., to be the ultimate judge for Congressional
        election disputes and of some Presidential election disputes. Congress
        also has quasi-judicial jurisdiction over impeachments of government
        employees whether or not they are elected, and over expulsions for cause
        of its own members and over other ethical sanctions of its own members.
        Many other legislatures have some sort of quansi-judicial impeachment
        and/or explusion power exercised as a whole by by some committee within
        it. It is common in the United States for administrative agencies,
        within their narrow area of competence to exercise both
        quasi-legislative power to enact regulations with a broad mandate in a
        subject area, and also to have quasi-judicial power in that same subject
        area. The Securities and Exchange Commission, the National Labor
        Relations Board, the Internal Revenue Service, the Environmental
        Protection Agency, and the Merit System Protection Board, for example,
        all operate in this fashion to some extent. Likewise, it is very common
        at the local government level for a city council and its planning board
        to carry out both legislative roles and quasi-judicial role when
        disputes come up regarding its land use regulations. Similarly, school
        boards routinely both establish employment regulations and other school
        rules, and serve in a quasi-judicial role with respect employee
        discipline or termination, and with respect to student discipline. This
        dual role is also common for the boards of other public institutions
        like hospitals and state colleges, and for private non-profit
        organizations. A recent example in that kind of situation is Colorado's
        State School Board which both exercises legislative power over when
        charter schools (i.e. public schools not under the direct supervision of
        any elected local school board) may be formed, and has the ultimate and
        final judicial review role over decisions by local school boards to
        grant or deny school charters.
      - >-
        It isn't explicitly prohibited so long as the amount claimed is in the
        aggregate less than $20,000. But, it would probably be better to file
        separately. First, very simple single party, single transaction cases
        are what small claims court is designed to do, and going against the
        flow often creates unforeseen confusion for the judge in the Justice
        Court who isn't a sophisticated civil litigation expert. The Justices of
        the Peace who preside over Justice Courts that handle small claims cases
        in Texas often aren't and don't have to be lawyers or even high school
        graduates. Second, if you sue as a group, and one of your group is the
        lead person handling the case (and that person isn't a lawyer), the lead
        person is at grave risk of being found to be practicing law without a
        license by taking actions in a lawsuit on behalf of your fellow
        plaintiffs.
  - source_sentence: >-
      Q: Myself & spouse have lived in home 27 years. If I file for divorce will
      he be made to sell home in St Pete and split the. Home in his name only.
      Do not trust him! 
    sentences:
      - >-
        A:As long as the house is a marital asset, which it sounds like it is,
        the court will order the equity to be divided as part of equitable
        distribution. You will each have the opportunity to buy the other out or
        else the property will be sold. Speak with a local family lawyer for
        more specific advice.
      - >-
        A:Hi there, good evening. In federal cases, such as yours in the Central
        District Court of California, once a case is e-filed, the documents,
        including the complaint and summons, can typically be downloaded from
        PACER. This is a common practice and allows for easy access to filed
        documents. A "conformed copy" of a document is essentially a copy that
        includes all signatures and official stamps, making it identical to the
        original. These copies are often required in situations where you need
        to submit a document that is as valid as the original, such as for
        certain legal or official proceedings. They ensure that the document
        you're using is a true and complete representation of the original filed
        document.
      - >-
        A:First off, they read him his rights once. Secondly, not reading your
        rights does not mean not guilty automatically, If Miranda is violated it
        only suppresses any statements made. He was not charged with underage
        drinking, curfew, truancy, or running away. He was charged with a
        criminal offense, DUI. Time to lawyer up. If he is convicted of DUI, he
        loses his license for a minimum of two years and then must have a
        hearing with the Secretary of State.
  - source_sentence: how private is this app?
    sentences:
      - >-
        We will not use this information for anything other than providing the
        Service for which the information was supplied.
      - >-
        ), and College Board program participants may provide information
        regarding study habits and test scores (e.g., the number of hours
        studied, modules or tests taken, scores earned, etc.
      - >-
        We share your information with Service Providers who process data on our
        behalf, such as credit card processors and customer management systems.
  - source_sentence: does this app may share my location anonymous?
    sentences:
      - >-
        You may opt out of certain ad targeting and retargeting services by
        visiting the Digital Advertising Alliances opt-out page, or the Network
        Advertising Initiatives opt-out page.
      - >-
        Delivery of location services will involve reference to one or more of
        the following: (a) the coordinates (latitude/longitude) of your
        location; (b) look-up of your country of location by reference to your
        IP address against public sources; and/or (c) your location settings on
        your Apple device or Android device, or similar device
        identifier/settings.
      - >-
        We may collect usage information about your use of our Service, such as
        the number of problems you have attempted, the number of videos you have
        viewed, and the amount of time spent to complete a problem.
datasets:
  - sentence-transformers/coliee
  - bwang0911/legal_qa_v1
  - bwang0911/law_stackexchange
  - bwang0911/legal_lens_nli
  - bwang0911/cuad_qa
  - bwang0911/privacy_qa
  - bwang0911/legal_case_summarization
  - bwang0911/aus_legal_qa
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - cosine_accuracy@1
  - cosine_accuracy@3
  - cosine_accuracy@5
  - cosine_accuracy@10
  - cosine_precision@1
  - cosine_precision@3
  - cosine_precision@5
  - cosine_precision@10
  - cosine_recall@1
  - cosine_recall@3
  - cosine_recall@5
  - cosine_recall@10
  - cosine_ndcg@10
  - cosine_mrr@10
  - cosine_map@100
model-index:
  - name: SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
    results:
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mteb/AILA casedocs
          type: mteb/AILA_casedocs
        metrics:
          - type: cosine_accuracy@1
            value: 0.24
            name: Cosine Accuracy@1
          - type: cosine_accuracy@3
            value: 0.4
            name: Cosine Accuracy@3
          - type: cosine_accuracy@5
            value: 0.44
            name: Cosine Accuracy@5
          - type: cosine_accuracy@10
            value: 0.5
            name: Cosine Accuracy@10
          - type: cosine_precision@1
            value: 0.24
            name: Cosine Precision@1
          - type: cosine_precision@3
            value: 0.2
            name: Cosine Precision@3
          - type: cosine_precision@5
            value: 0.14400000000000002
            name: Cosine Precision@5
          - type: cosine_precision@10
            value: 0.096
            name: Cosine Precision@10
          - type: cosine_recall@1
            value: 0.06261421911421912
            name: Cosine Recall@1
          - type: cosine_recall@3
            value: 0.1773951048951049
            name: Cosine Recall@3
          - type: cosine_recall@5
            value: 0.21672843822843824
            name: Cosine Recall@5
          - type: cosine_recall@10
            value: 0.28030419580419585
            name: Cosine Recall@10
          - type: cosine_ndcg@10
            value: 0.23571318760075094
            name: Cosine Ndcg@10
          - type: cosine_mrr@10
            value: 0.32385714285714284
            name: Cosine Mrr@10
          - type: cosine_map@100
            value: 0.19099315576955767
            name: Cosine Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mteb/AILA statutes
          type: mteb/AILA_statutes
        metrics:
          - type: cosine_accuracy@1
            value: 0.24
            name: Cosine Accuracy@1
          - type: cosine_accuracy@3
            value: 0.52
            name: Cosine Accuracy@3
          - type: cosine_accuracy@5
            value: 0.72
            name: Cosine Accuracy@5
          - type: cosine_accuracy@10
            value: 0.8
            name: Cosine Accuracy@10
          - type: cosine_precision@1
            value: 0.24
            name: Cosine Precision@1
          - type: cosine_precision@3
            value: 0.20666666666666667
            name: Cosine Precision@3
          - type: cosine_precision@5
            value: 0.19999999999999996
            name: Cosine Precision@5
          - type: cosine_precision@10
            value: 0.144
            name: Cosine Precision@10
          - type: cosine_recall@1
            value: 0.068
            name: Cosine Recall@1
          - type: cosine_recall@3
            value: 0.16066666666666665
            name: Cosine Recall@3
          - type: cosine_recall@5
            value: 0.25033333333333335
            name: Cosine Recall@5
          - type: cosine_recall@10
            value: 0.35100000000000003
            name: Cosine Recall@10
          - type: cosine_ndcg@10
            value: 0.2945290400206784
            name: Cosine Ndcg@10
          - type: cosine_mrr@10
            value: 0.4145238095238095
            name: Cosine Mrr@10
          - type: cosine_map@100
            value: 0.23863257355862635
            name: Cosine Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mteb/legalbench consumer contracts qa
          type: mteb/legalbench_consumer_contracts_qa
        metrics:
          - type: cosine_accuracy@1
            value: 0.48737373737373735
            name: Cosine Accuracy@1
          - type: cosine_accuracy@3
            value: 0.6515151515151515
            name: Cosine Accuracy@3
          - type: cosine_accuracy@5
            value: 0.73989898989899
            name: Cosine Accuracy@5
          - type: cosine_accuracy@10
            value: 0.8560606060606061
            name: Cosine Accuracy@10
          - type: cosine_precision@1
            value: 0.48737373737373735
            name: Cosine Precision@1
          - type: cosine_precision@3
            value: 0.21717171717171713
            name: Cosine Precision@3
          - type: cosine_precision@5
            value: 0.14797979797979796
            name: Cosine Precision@5
          - type: cosine_precision@10
            value: 0.0856060606060606
            name: Cosine Precision@10
          - type: cosine_recall@1
            value: 0.48737373737373735
            name: Cosine Recall@1
          - type: cosine_recall@3
            value: 0.6515151515151515
            name: Cosine Recall@3
          - type: cosine_recall@5
            value: 0.73989898989899
            name: Cosine Recall@5
          - type: cosine_recall@10
            value: 0.8560606060606061
            name: Cosine Recall@10
          - type: cosine_ndcg@10
            value: 0.6575720798646046
            name: Cosine Ndcg@10
          - type: cosine_mrr@10
            value: 0.5956780102613435
            name: Cosine Mrr@10
          - type: cosine_map@100
            value: 0.6021553873830202
            name: Cosine Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mteb/legalbench corporate lobbying
          type: mteb/legalbench_corporate_lobbying
        metrics:
          - type: cosine_accuracy@1
            value: 0.788235294117647
            name: Cosine Accuracy@1
          - type: cosine_accuracy@3
            value: 0.9205882352941176
            name: Cosine Accuracy@3
          - type: cosine_accuracy@5
            value: 0.9382352941176471
            name: Cosine Accuracy@5
          - type: cosine_accuracy@10
            value: 0.9588235294117647
            name: Cosine Accuracy@10
          - type: cosine_precision@1
            value: 0.788235294117647
            name: Cosine Precision@1
          - type: cosine_precision@3
            value: 0.3068627450980392
            name: Cosine Precision@3
          - type: cosine_precision@5
            value: 0.1876470588235294
            name: Cosine Precision@5
          - type: cosine_precision@10
            value: 0.09588235294117646
            name: Cosine Precision@10
          - type: cosine_recall@1
            value: 0.788235294117647
            name: Cosine Recall@1
          - type: cosine_recall@3
            value: 0.9205882352941176
            name: Cosine Recall@3
          - type: cosine_recall@5
            value: 0.9382352941176471
            name: Cosine Recall@5
          - type: cosine_recall@10
            value: 0.9588235294117647
            name: Cosine Recall@10
          - type: cosine_ndcg@10
            value: 0.8823720261303867
            name: Cosine Ndcg@10
          - type: cosine_mrr@10
            value: 0.8569596171802053
            name: Cosine Mrr@10
          - type: cosine_map@100
            value: 0.8589677781368958
            name: Cosine Map@100
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: mteb/legal summarization
          type: mteb/legal_summarization
        metrics:
          - type: cosine_accuracy@1
            value: 0.4788732394366197
            name: Cosine Accuracy@1
          - type: cosine_accuracy@3
            value: 0.6373239436619719
            name: Cosine Accuracy@3
          - type: cosine_accuracy@5
            value: 0.721830985915493
            name: Cosine Accuracy@5
          - type: cosine_accuracy@10
            value: 0.8204225352112676
            name: Cosine Accuracy@10
          - type: cosine_precision@1
            value: 0.4788732394366197
            name: Cosine Precision@1
          - type: cosine_precision@3
            value: 0.23474178403755866
            name: Cosine Precision@3
          - type: cosine_precision@5
            value: 0.16830985915492958
            name: Cosine Precision@5
          - type: cosine_precision@10
            value: 0.1028169014084507
            name: Cosine Precision@10
          - type: cosine_recall@1
            value: 0.4233891988293397
            name: Cosine Recall@1
          - type: cosine_recall@3
            value: 0.5632004146088653
            name: Cosine Recall@3
          - type: cosine_recall@5
            value: 0.6415233827205657
            name: Cosine Recall@5
          - type: cosine_recall@10
            value: 0.7539452624839948
            name: Cosine Recall@10
          - type: cosine_ndcg@10
            value: 0.602922176130265
            name: Cosine Ndcg@10
          - type: cosine_mrr@10
            value: 0.5816705790297337
            name: Cosine Mrr@10
          - type: cosine_map@100
            value: 0.5513678334926079
            name: Cosine Map@100

SentenceTransformer based on sentence-transformers/all-mpnet-base-v2

This is a sentence-transformers model finetuned from sentence-transformers/all-mpnet-base-v2 on the coliee, legal_qa, law_stack, legal_lens, cuad_qa, privacy_qa, legal_sum and aus_legal_qa datasets. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

Model Type: Sentence Transformer
Base model: sentence-transformers/all-mpnet-base-v2
Maximum Sequence Length: 192 tokens
Output Dimensionality: 768 dimensions
Similarity Function: Cosine Similarity
Training Datasets:
- coliee
- legal_qa
- law_stack
- legal_lens
- cuad_qa
- privacy_qa
- legal_sum
- aus_legal_qa
Language: en

Model Sources

Documentation: Sentence Transformers Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 192, 'do_lower_case': False}) with Transformer model: MPNetModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("bwang0911/jev2-legal")
# Run inference
sentences = [
    'does this app may share my location anonymous?',
    'Delivery of location services will involve reference to one or more of the following: (a) the coordinates (latitude/longitude) of your location; (b) look-up of your country of location by reference to your IP address against public sources; and/or (c) your location settings on your Apple device or Android device, or similar device identifier/settings.',
    'We may collect usage information about your use of our Service, such as the number of problems you have attempted, the number of videos you have viewed, and the amount of time spent to complete a problem.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Evaluation

Metrics

Information Retrieval

Datasets: mteb/AILA_casedocs, mteb/AILA_statutes, mteb/legalbench_consumer_contracts_qa, mteb/legalbench_corporate_lobbying and mteb/legal_summarization
Evaluated with InformationRetrievalEvaluator

Metric	mteb/AILA_casedocs	mteb/AILA_statutes	mteb/legalbench_consumer_contracts_qa	mteb/legalbench_corporate_lobbying	mteb/legal_summarization
cosine_accuracy@1	0.24	0.24	0.4874	0.7882	0.4789
cosine_accuracy@3	0.4	0.52	0.6515	0.9206	0.6373
cosine_accuracy@5	0.44	0.72	0.7399	0.9382	0.7218
cosine_accuracy@10	0.5	0.8	0.8561	0.9588	0.8204
cosine_precision@1	0.24	0.24	0.4874	0.7882	0.4789
cosine_precision@3	0.2	0.2067	0.2172	0.3069	0.2347
cosine_precision@5	0.144	0.2	0.148	0.1876	0.1683
cosine_precision@10	0.096	0.144	0.0856	0.0959	0.1028
cosine_recall@1	0.0626	0.068	0.4874	0.7882	0.4234
cosine_recall@3	0.1774	0.1607	0.6515	0.9206	0.5632
cosine_recall@5	0.2167	0.2503	0.7399	0.9382	0.6415
cosine_recall@10	0.2803	0.351	0.8561	0.9588	0.7539
cosine_ndcg@10	0.2357	0.2945	0.6576	0.8824	0.6029
cosine_mrr@10	0.3239	0.4145	0.5957	0.857	0.5817
cosine_map@100	0.191	0.2386	0.6022	0.859	0.5514

Training Details

Training Datasets

coliee

Dataset: coliee at d90012e
Size: 9,260 training samples
Columns: anchor, positive, and negative

Approximate statistics based on the first 1000 samples:

	anchor	positive	negative
type	string	string	string
details	min: 11 tokens mean: 41.76 tokens max: 99 tokens	min: 25 tokens mean: 119.1 tokens max: 192 tokens	min: 14 tokens mean: 113.91 tokens max: 192 tokens

Samples:

anchor	positive	negative
`A compulsory auction is also a sale, so warranty is imposed the same as for an ordinary sale.`	Article 568 (1) The successful bidder at an auction based on the provisions of the Civil Execution Act and other laws (hereinafter referred to as an "auction" in this Article) may cancel the contract or demand a reduction of the price against the obligor pursuant to the provisions of Articles 541 and 542 and the provisions of Article 563 (including as applied mutatis mutandis pursuant to Article 565). (2) In the cases referred to in the preceding paragraph, if the obligor is insolvent, the successful bidder may demand total or partial reimbursement of the proceeds against the obligees that received the distribution of the proceeds. (3) In the cases set forth in the preceding two paragraphs, if obligors knew of the absence of the object or right and did not disclose the same, or if obligees knew of the absence but demanded an auction, the successful bidder may claim compensation for loss or damage against those persons. (4) The provisions of the preceding three paragraphs do not apply ...	`Article 575 (1) If the subject matter of a sale which has not yet been delivered bears fruits, the fruits vest in the seller. (2) The buyer bears the obligation to pay interest on the price beginning from the day of delivery;provided, however, that if a due date is provided for the payment of the price, it is not necessary to pay the interest until that due date arrives..`
`A compulsory auction is also a sale, so warranty is imposed the same as for an ordinary sale.`	Article 568 (1) The successful bidder at an auction based on the provisions of the Civil Execution Act and other laws (hereinafter referred to as an "auction" in this Article) may cancel the contract or demand a reduction of the price against the obligor pursuant to the provisions of Articles 541 and 542 and the provisions of Article 563 (including as applied mutatis mutandis pursuant to Article 565). (2) In the cases referred to in the preceding paragraph, if the obligor is insolvent, the successful bidder may demand total or partial reimbursement of the proceeds against the obligees that received the distribution of the proceeds. (3) In the cases set forth in the preceding two paragraphs, if obligors knew of the absence of the object or right and did not disclose the same, or if obligees knew of the absence but demanded an auction, the successful bidder may claim compensation for loss or damage against those persons. (4) The provisions of the preceding three paragraphs do not apply ...	`Article 596 The provisions of Article 551 apply mutatis mutandis to loans for use. Article 551 (1) The donor is presumed to have promised to deliver or transfer the thing or right that is the subject matter of the gift, while maintaining its condition as of the time when it is specified as the subject matter of the gift. (2) With respect to gifts with burden, the donor provides the same warranty as that of a seller, to the extent of that burden..`
`A compulsory auction is also a sale, so warranty is imposed the same as for an ordinary sale.`	Article 568 (1) The successful bidder at an auction based on the provisions of the Civil Execution Act and other laws (hereinafter referred to as an "auction" in this Article) may cancel the contract or demand a reduction of the price against the obligor pursuant to the provisions of Articles 541 and 542 and the provisions of Article 563 (including as applied mutatis mutandis pursuant to Article 565). (2) In the cases referred to in the preceding paragraph, if the obligor is insolvent, the successful bidder may demand total or partial reimbursement of the proceeds against the obligees that received the distribution of the proceeds. (3) In the cases set forth in the preceding two paragraphs, if obligors knew of the absence of the object or right and did not disclose the same, or if obligees knew of the absence but demanded an auction, the successful bidder may claim compensation for loss or damage against those persons. (4) The provisions of the preceding three paragraphs do not apply ...	`Article 520 If a claim and obligation becomes vested in the same person, such claim is extinguished;provided, however, that this does not apply if such a claim is the subject matter of the right of a third party..`

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

legal_qa

Dataset: legal_qa at bbe3790
Size: 3,742 training samples
Columns: anchor and positive
Approximate statistics based on the first 1000 samples:
anchor positive
type string string
details
min: 13 tokens
mean: 108.12 tokens
max: 192 tokens

min: 6 tokens
mean: 130.94 tokens
max: 192 tokens

	anchor	positive
type	string	string
details	min: 13 tokens mean: 108.12 tokens max: 192 tokens	min: 6 tokens mean: 130.94 tokens max: 192 tokens

Samples:

anchor	positive
Q: I was wondering if a pain management office is acting illegally/did an illegal action.. I was discharged as a patient from a pain management office after them telling me that a previous pain management specialist I saw administered a steroid shot wrong and I told them in the portal that I spoke to lawyers for advice but no lawsuit/case was created. It was maybe 1-2 months after I was discharged that I no longer have access to my patient portal with them. Every time I try to login I enter my credentials, wait a few seconds, and then I get re-directed back to the original screen where I have various options to login. I know I can speak to the office directly and ask them about what specifically is going on, talk to other lawyers if this is a violation of my rights, etc. but I was just wondering if anyone on this site would know if this action is in fact illegal.	A:In Kentucky, your situation raises questions about patient rights and medical records access. If you were discharged from a pain management office and subsequently lost access to your patient portal, it's important to understand your rights regarding medical records. Under the Health Insurance Portability and Accountability Act (HIPAA), you have the right to access your own medical records. A healthcare provider cannot deny you access to your records, even if you were discharged from their practice. The issue with the patient portal could be a technical glitch or a deliberate action, but either way, it needs to be addressed. You should contact the pain management office directly to inquire about the issue with the patient portal. They are obligated to provide you with a way to access your medical records, which may include providing paper copies or access through a different electronic means. If the office is unresponsive or refuses to provide access to your records, consider speakin...
Q: My houseboat was moved while I was at work and was asked to leave the property after 16 months without any notices.. Management told me that he didn’t like those kind of people that came to visit me. I went on vacation and when I came back my electrical cord was missing and my water hose was cut in pieces. He than got of hold of me and said I have your boat and that he was putting a lien on it for back rent. I never received any notices from management. He than told me that he wanted me to leave the property and that he would hold my boat until i found another parking spot for it. I finally found a parking spot a year later and I find out that he liened my houseboat and was selling it and told me to sue him and gave me his lawyers contact. What options do I have. I now am homeless and I lost my job and seeing myself falling as time goes. Any help would be appreciated.	A:If your houseboat was moved without your permission and you were asked to leave the property after 16 months without any notices, and the management has placed a lien on your houseboat and is attempting to sell it, you may have legal options to challenge their actions. First, you may want to consult with an attorney who specializes in property law or landlord-tenant law to review your case and provide guidance on your legal rights and options. It may also be helpful to gather any evidence you have, such as receipts or documentation of payments or communications with the management, to support your case. Some potential legal claims you may have against the management include breach of contract, conversion, or wrongful eviction. These claims may allow you to seek damages or other forms of relief, such as the return of your houseboat or compensation for any losses you have suffered. It's important to act quickly, as there may be deadlines or other requirements for filing a legal claim. ...
`Q: Wondering if I could sue a dealership if I’ve had to replace my transmission 2 times within a year. I’ve had to replace my transmission now 2 different times in 10 months of owning my 2018 Ford Expedition. My first replacement was $5,200 and then 1 1/2 months later the transmission went out and now they are working on it again`	A:Yes, you can sue a dealership if you have had to replace your transmission 2 times within a year. Whether you will be successful depends on the facts and your presentation. You don't mention anything about any written agreements. Allowing an attorney to evaluate, organize and draft your conciliation or (small claims) complaint (up to $15,000) would be a wise investment. A well polished complaint will not only provide the judge a solid foundation to rule in your favor, but a detailed outline on which to base your oral argument. It would provide you a distinct advantage over the opposing party. The fees can be reasonable depending on the attorney.

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

law_stack

Dataset: law_stack at b19a371
Size: 13,000 training samples
Columns: anchor and positive
Approximate statistics based on the first 1000 samples:
anchor positive
type string string
details
min: 27 tokens
mean: 141.93 tokens
max: 192 tokens

min: 15 tokens
mean: 166.18 tokens
max: 192 tokens

	anchor	positive
type	string	string
details	min: 27 tokens mean: 141.93 tokens max: 192 tokens	min: 15 tokens mean: 166.18 tokens max: 192 tokens

Samples:

anchor	positive
`Why is drunk driving causing accident punished so much worse than just drunk driving? When people drink and drive and then cause an accident especially where if someone dies they get years and years in prison but just the act of drunk driving is punished way more lenient. Shouldn't the 2, drunk driving and drunk driving then causing accident be similarly punished? I feel like a lot of times it's luck whether an accident happens.`	Moral luck You have raised the issue of moral luck, a long recognized problem in criminal theory. The classic expositions of this issue are by Thomas Nagel, in his chapter, "Moral Luck" (1979) and Bernard Williams, "Moral Luck" (1976). Specifically, you are describing what they call outcome luck, or consequential luck. Driving while intoxicated vs. driving while intoxicated and causing death is not the only example where moral luck results in a distinction in punishment. Other examples are: dangerous driving vs. dangerous driving that causes death a successful offence vs. an attempted offence (generally resulting in a maximum sentence less than that of the successful offence) Nagel writes: If someone has had too much to drink and his car swerves on to the sidewalk, he can count himself morally lucky if there are no pedestrians in its path. If there were, he would be to blame for their deaths, and would probably be prosecuted for manslaughter. But if he hurts no one,...
Question Concerning Responding to Employer of Minor Daughter Paid Under Minimum Wage My high school daughter worked for about a year for an employer who owns a tutoring company in our town. Due to friction between my daughter and the employer, my daughter recently quit but she realized that she was being underpaid for much of this year (2023) because the minimum wage here in California is currently $15.50 for 2023 but she was still getting paid $14.00, the California minimum wage for 2022, when she recently quit (in August 2023). Now according to my daughter there is a provision in California law which allows employers to pay only 85% of minimum wage for new workers with no prior experience for their first 160 hours of work. For 2023, that "new worker" wage level would work out to $13.17 per hour, but my daughter said that she exceeded her first 160 hours of work for the employer back in March 2023. So, basically, my daughter was being paid under the proper CA 2023 minimum wa...	Read the terms It’s quite likely that, if you took this to court, the employer would be liable to pay your daughter interest on the underpayment and possibly be fined by the state for failing to follow the law. The terms probably are offering to pay the back pay with no interest and your daughter agreeing to confidentiality about the breach. Probably - I haven’t read them. In other words, they’re asking her to sign a contract saying she gets $XXX now, and can’t make any further claims against them. Such releases are commonplace when setting a dispute and there’s probably nothing underhanded going on. Probably - I haven’t read them. Because minors can void contracts if they are not in their interest, they want you, as her legal guardian, to also sign so that can’t happen. A relatively prudent precaution on their part. The alternative is to not sign the document and they presumably won’t pay. It will then be up to you whether to sue them which will cost you money, possibly more than you ...
`Can Hawaii secede from the U.S. through legal means? Can Hawaii secede from the U.S. through legal means or is it forbidden by U.S. law? I am asking, because I doubt the U.S. would accept the result of a referendum that rules that the Hawaiians want to secede from the U.S. just like Russia or China wouldn't accept it.`	Currently, there is no legal means for a state to secede form the U.S. A quick Google search yields So you want to secede from the U.S.: A four-step guide - The Washington Post: "When the Confederate states seceded in 1861 and were then defeated in the Civil War, the argument is that they demonstrated that you can't secede from the Union. The 1869 Supreme Court case TEXAS v. WHITE ET AL (Legal Information Institute) determined that the secession was never actually a real thing in the eyes of the federal government. The Confederate States of America wasn't an independent country any more than your house is its own country simply because you say it is. 'The Constitution, in all its provisions,' the justices wrote, 'looks to an indestructible Union composed of indestructible States.'" Also from that Post piece: In 2006, Justice Antonin Scalia was asked by screenwriter Dan Turkewitz if the idea of Maine seceding from the country made sense as a possible plot point. Scalia, perhap...

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

legal_lens

Dataset: legal_lens at a4c8193
Size: 107 training samples
Columns: anchor and positive
Approximate statistics based on the first 107 samples:
anchor positive
type string string
details
min: 107 tokens
mean: 164.29 tokens
max: 192 tokens

min: 27 tokens
mean: 78.31 tokens
max: 192 tokens

	anchor	positive
type	string	string
details	min: 107 tokens mean: 164.29 tokens max: 192 tokens	min: 27 tokens mean: 78.31 tokens max: 192 tokens

Samples:

anchor	positive
DEFENDANT has agreed to a $72,250 settlement to resolve claims that it violated Illinois' Biometric Information Privacy Act (BIPA) by scanning the hands and fingerprints of its employees without obtaining prior consent. The settlement benefits employees in Illinois who had their fingers or hands scanned by a timekeeping system between Dec. 31, 2015, and Dec. 31, 2020, without first signing a consent form. Although DEFENDANT has not admitted any wrongdoing, it agreed to the settlement to resolve the BIPA allegations. Class members can receive an equal share of the net settlement fund, estimated to be around $352.75 per worker. The deadline for exclusion and objection is May 15, 2023, and the final approval hearing for the BIPA settlement is scheduled for June 15, 2023. No claim form is required to benefit from the settlement.	Y'know, it's funny how things turn out sometimes. I was working this job, right? Nothing fancy, just clocking in and out, doing my thing. They had this newfangled tech system for logging our hours, some sort of hand scan thing. Thought it was pretty cool, not gonna lie. High-tech, right? Made me feel like I was in a sci-fi movie or something. But then, things started to get a bit weird. I mean, I didn't notice anything at first, but after a while, it kinda felt off, y'know? Like, I couldn't shake the feeling that something was not right. I mean, it's just a hand scanner, right? What could possibly go wrong? And then, outta nowhere, I heard this rumor going around about some sort of issue with the hand scanner. Something about not getting the proper consents or something. It was all a bit hush-hush, and no one was really talking about it openly. But you know how these things go, word gets around. So here I am, just trying to do my job, and suddenly I'm in the middle of some sort of t...
DEFENDANT has agreed to pay $6.5 million to settle a nationwide class action lawsuit, which accused the company of making telemarketing calls in violation of the Telephone Consumer Protection Act (TCPA). The lawsuit, filed in 2015, alleged that the company made calls using a prerecorded message to cell phones, residential lines, and numbers on the National Do-Not-Call Registry to obtain new clients. The settlement includes cash payments of between $100 and $150 to eligible members of the class action, as well as covering class administration costs, plaintiffs’ attorneys’ fees and litigation costs up to $2,210,566. A $25,000 court-approved service award will also be given to the plaintiff. DEFENDANT will also implement policies and procedures to prevent future violations. Despite the settlement, DEFENDANT does not admit to any wrongdoing and continues to deny the allegations.	`Unsolicited calls? They're a real nuisance. It seems my number made it onto a list somewhere, and now my phone won't stop ringing with offers I never asked for.`
DEFENDANT has agreed to a $8.5 million class action settlement over allegations that its stores used misleading price tags. The lawsuit alleged that the use of the phrase “Compare At” on price tags was deceptive, as it misled customers about the actual price of comparable items at other stores. Customers who purchased items from DEFENDANT's stores in California between July 17, 2011 and Dec. 6, 2017, can file a claim to receive either a merchandise store credit or cash from the settlement. DEFENDANT has also agreed to change pricing disclosures on its website and in its California stores to comply with the state's price comparison advertising regulations. The settlement was granted preliminary approval on Dec. 5, 2017, and class members have until April 9, 2018 to object or opt out.	`Got a bargain at my favourite shop, but the "Compare At" tags sure had me thinking other places were pricier. Hmm, interesting marketing strategy!`

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

cuad_qa

Dataset: cuad_qa at 333b657
Size: 11,180 training samples
Columns: anchor and positive
Approximate statistics based on the first 1000 samples:
anchor positive
type string string
details
min: 33 tokens
mean: 51.31 tokens
max: 105 tokens

min: 3 tokens
mean: 57.1 tokens
max: 192 tokens

	anchor	positive
type	string	string
details	min: 33 tokens mean: 51.31 tokens max: 105 tokens	min: 3 tokens mean: 57.1 tokens max: 192 tokens

Samples:

anchor	positive
`Highlight the parts (if any) of this contract related to "Document Name" that should be reviewed by a lawyer. Details: The name of the contract`	`DISTRIBUTOR AGREEMENT`
`Highlight the parts (if any) of this contract related to "Parties" that should be reviewed by a lawyer. Details: The two or more parties who signed the contract`	`Distributor`
`Highlight the parts (if any) of this contract related to "Parties" that should be reviewed by a lawyer. Details: The two or more parties who signed the contract`	`Electric City of Illinois L.L.C.`

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

privacy_qa

Dataset: privacy_qa at cd59571
Size: 6,038 training samples
Columns: anchor and positive
Approximate statistics based on the first 1000 samples:
anchor positive
type string string
details
min: 6 tokens
mean: 11.54 tokens
max: 30 tokens

min: 4 tokens
mean: 30.25 tokens
max: 143 tokens

	anchor	positive
type	string	string
details	min: 6 tokens mean: 11.54 tokens max: 30 tokens	min: 4 tokens mean: 30.25 tokens max: 143 tokens

Samples:

anchor	positive
`do you share my location with other people`	`To use our Applications, you must have an account with a healthcare provider who uses Epic's software and your use of our Applications is also subject to your healthcare provider's privacy policy.`
`are you selling my data`	`Interest Based Advertising Khan Academy does not display any targeted advertising on our Service.`
`will the data collected from my usage of the app be sold to third parties?`	`Additionally, if you choose to participate in our member-to-member communications programs, other TripAdvisor members may contact you by using TripAdvisor as an intermediary; however, TripAdvisor will not share your email address with any other members nor display it any public manner.`

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

legal_sum

Dataset: legal_sum at 667db49
Size: 7,773 training samples
Columns: anchor and positive
Approximate statistics based on the first 1000 samples:
anchor positive
type string string
details
min: 192 tokens
mean: 192.0 tokens
max: 192 tokens

min: 63 tokens
mean: 191.26 tokens
max: 192 tokens

	anchor	positive
type	string	string
details	min: 192 tokens mean: 192.0 tokens max: 192 tokens	min: 63 tokens mean: 191.26 tokens max: 192 tokens

Samples:

anchor	positive
Appeal No. LXVI of 1949. Appeal from the High Court of judicature, Bombay, in a reference under section 66 of the Indian Income tax Act, 1022. K.M. Munshi (N. P. Nathvani, with him), for the appel lant. ' M.C. Setalvad, Attorney General for India (H. J. Umrigar, with him), for the respondent. 1950. May 26. The judgment of the Court was delivered by MEHR CHAND MAHAJAN J. This is an appeal against a judgment of the High Court of Judicature at Bombay in an income tax matter and it raises the question whether munici pal property tax and urban immoveable property tax payable under the relevant Bombay Acts are allowable deductions under section 9 (1) (iv) of the Indian Income tax Act. The assessee company is an investment company deriving its income from properties in the city of Bombay. For the assessment year 1940 41 the net income of the assessee under the head "property" was computed by the Income tax Officer in the sum of Rs. 6,21,764 after deducting from gross rents certain payments. T...	The charge created in respect of municipal property tax by section 212 of the City of Bombay Municipal Act, 1888, is an "annual charge not being a capital charge" within the mean ing of section 9 (1) (iv) of the Indian Income tax Act, 199.2, and the amount of such charge should therefore be deducted in computing the income from such property for the purposes of section 9 of the Indian Income tax Act. The charge in respect of urban immoveable property tax created by the Bombay Finance Act, 1939 is similar in character and the amount of such charge should also be deducted. The expression "capital charge" in s.9(1) (iv) means a charge created for a capital sum,that is to say, a charge created to. ' secure the discharge of a liability of a capi tal nature; and an "annual charge" means a charge to secure an annual liabili ty. 554
Civil Appeal No.94 of 1949. 107 834 Appeal from a judgment and decree of the High Court of Judi cature at Patna in Appeal from Appellate Decree No. 97 of 1946 (Mannohar Lall and Mukherji JJ.) dated 23rd Decem ber, 1947, confirming the judgment of the District Judge of Purulia in Appeal No. 159 of 1944. S.P. Sinha (P. K. Bose, with him) for the appel lant. N.C. Chatterjee and Panchanan Ghosh (Chandra Narayan Naik, with them) for the respondent. 1950. December 1. The Judgment of the Court was deliv ered by PATANJALI SASTRI J. This appeal arises out of a suit brought by the respondent in the court of the Subordinate Judge, Dhanbad, for recovery of arrears of royalty and cess from the appellant and another alleged to be due under a compromise decree passed on the 6th March, 1923, in a previ ous suit between the predecessors in interest of the par ties. The only plea which is material for the purpose of this appeal is that the compromise decree not having been registered was inadmissible in...	An agreement for a lease, which a lease is by the Indian declared to include, must be a document which effects an actual demise and operates as a lease. It must create present and immediate interest in land. Where a litigation between two persons A and B who claimed to be tenants under C was settled by a compromise decree the effect of which was to create a perpetual underlease between A and B which was to take effect only on condition that A paid Rs. 8,000 to C within a fixed period: Held, that such a contingent agreement was not "a lease" within el. (a) of section 17 (t) of the Indian , and even though it was covered by cl. (b) of the said sec tion it was exempt from registration under el. (vi) of subs. (2) of section 17. Hemanta Kumari Debi vs Midnapur Zamindari Co. (I P.C.) relied on.
iminal Appeal No. 40 of 1951, 127 Appeal from the Judgment and Order dated the 1st June, 1951, of the High Court of Judicature in Assam (Thadani C.J. and Ram Labhaya J.,) in Criminal Reference No. I of 1951, arising out of Judgment and Order dated the 15th November, 1950, of the Court of the Additional District Magistrate, Lakhimpur, in Case No. 1126C of 1950. Jindra Lal for the appellant. Nuruddin Ahmed for the respondent. October 23. The Judgment of the Court was delivered by CHANDRASEKHARA AIYAR J. Rameshwar Bhartia, the appellant, is a shopkeeper in Assam. He was prosecuted for storing paddy without a licence in excess of the quantity permitted by the Assam Food Grains Control Order, 1947. He admitted storage and possession of 550 maunds of paddy, but pleaded that he did not know that any licence was necessary. The 'Additional District Magistrate recorded a plea of guilty, but imposed him a fine of Rs. 50 only, as he considered his ignorance of the provisions of the Food Grains Con...	The question whether a Magistrate is "personally interested" in a ease within the meaning of section 556, Criminal Procedure Code, has essentially to be decided the facts of each case. Where an officer as a District Magistrate exercising his powers under section 7(1) of the Essential Supplies (Temporary Powers) Act, 1946, sanctioned the prosecution of a person for violation of sections 3 and 7 of the Assam Food Grains Control Order, 1947, and the same officer as Additional District Magistrate tried and convicted the accused, and it was contended that as the officer had given sanction for prosecution he was "personally interested" in the case within the meaning of section 656, Criminal Procedure Code, and the trial and conviction were therefore illegal: Held, that bymerely giving sanction for prosecution he did not become personally interested" in the case and the trial and conviction were not illegal. In both cases of sanction and direction to prosecute, an application of the mind is n...

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

aus_legal_qa

Dataset: aus_legal_qa at 0628f4a
Size: 2,124 training samples
Columns: anchor and positive
Approximate statistics based on the first 1000 samples:
anchor positive
type string string
details
min: 12 tokens
mean: 38.68 tokens
max: 106 tokens

min: 21 tokens
mean: 111.75 tokens
max: 192 tokens

	anchor	positive
type	string	string
details	min: 12 tokens mean: 38.68 tokens max: 106 tokens	min: 21 tokens mean: 111.75 tokens max: 192 tokens

Samples:

anchor	positive
`In the case of Nasr v NRMA Insurance [2006] NSWSC 1018, why was the plaintiff's appeal lodged out of time?`	`In Nasr v NRMA Insurance [2006] NSWSC 1018, the plaintiff's appeal was lodged out of time because the summons was filed on 8 June 2006, seven months after the decision of the Local Court was made on 4 October 2005. No explanation was provided for this delay.`
`In the case of R v NGUYEN [2001] NSWCCA 334, what was the relationship between the Appellant and Mr Nguyen, and what activities of Mr Nguyen did the Appellant testify about?`	In the case of R v NGUYEN [2001] NSWCCA 334, the Appellant testified that Mr Nguyen was her cousin and that she had allowed him to live in her flat for about 4 or 5 days. She stated that she had heard that Mr Nguyen was selling heroin and that she had seen him hand over a small foil to a third person, an event that made her feel surprised, upset, and angry. Despite her protests, Mr Nguyen allegedly continued to sell heroin from the flat. The Appellant also mentioned seeing other customers in the flat and a friend of Mr Nguyen's cutting foil in the lounge-room. Despite her complaints to her boyfriend and an aunt, she took no further steps to prevent these activities, citing reasons such as their close familial relationship and her reluctance to involve the police.
`In the case of Moore v Scenic Tours Pty Ltd [2015] NSWSC 237, what was the court's decision regarding the motion to restrain a firm from acting?`	`In the case of Moore v Scenic Tours Pty Ltd [2015] NSWSC 237, the court decided to dismiss the motion to restrain a firm from acting. The court found that the plaintiff was entitled to a solicitor of their choice and it was not in the interest of justice to deprive the plaintiff of their choice of solicitor.`

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 50.0,
    "similarity_fct": "cos_sim"
}

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 64
learning_rate: 1e-06
num_train_epochs: 2
warmup_ratio: 0.1
fp16: True
batch_sampler: no_duplicates

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
prediction_loss_only: True
per_device_train_batch_size: 64
per_device_eval_batch_size: 8
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
torch_empty_cache_steps: None
learning_rate: 1e-06
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1.0
num_train_epochs: 2
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
restore_callback_states_from_checkpoint: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 42
data_seed: None
jit_mode_eval: False
use_ipex: False
bf16: False
fp16: True
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: False
dataloader_num_workers: 0
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: False
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
ddp_find_unused_parameters: None
ddp_bucket_cap_mb: None
ddp_broadcast_buffers: False
dataloader_pin_memory: True
dataloader_persistent_workers: False
skip_memory_metrics: True
use_legacy_prediction_loop: False
push_to_hub: False
resume_from_checkpoint: None
hub_model_id: None
hub_strategy: every_save
hub_private_repo: False
hub_always_push: False
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
eval_do_concat_batches: True
fp16_backend: auto
push_to_hub_model_id: None
push_to_hub_organization: None
mp_parameters:
auto_find_batch_size: False
full_determinism: False
torchdynamo: None
ray_scope: last
ddp_timeout: 1800
torch_compile: False
torch_compile_backend: None
torch_compile_mode: None
dispatch_batches: None
split_batches: None
include_tokens_per_second: False
include_num_input_tokens_seen: False
neftune_noise_alpha: None
optim_target_modules: None
batch_eval_metrics: False
eval_on_start: False
use_liger_kernel: False
eval_use_gather_object: False
prompts: None
batch_sampler: no_duplicates
multi_dataset_batch_sampler: proportional

Training Logs

Epoch	Step	Training Loss	mteb/AILA_casedocs_cosine_ndcg@10	mteb/AILA_statutes_cosine_ndcg@10	mteb/legalbench_consumer_contracts_qa_cosine_ndcg@10	mteb/legalbench_corporate_lobbying_cosine_ndcg@10	mteb/legal_summarization_cosine_ndcg@10
0	0	-	0.1704	0.2351	0.6781	0.8793	0.5766
0.1196	100	-	0.1709	0.2434	0.6791	0.8834	0.5820
0.2392	200	-	0.2164	0.2702	0.6808	0.8832	0.6015
0.3589	300	-	0.2221	0.2707	0.6739	0.8855	0.6089
0.4785	400	-	0.2170	0.2705	0.6681	0.8857	0.6149
0.5981	500	2.757	0.2138	0.2644	0.6711	0.8830	0.6116
0.7177	600	-	0.2124	0.2725	0.6671	0.8861	0.6142
0.8373	700	-	0.2235	0.2919	0.6656	0.8856	0.6112
0.9569	800	-	0.2258	0.2902	0.6632	0.8848	0.6128
1.0766	900	-	0.2220	0.2999	0.6597	0.8865	0.6120
1.1962	1000	1.6406	0.2264	0.3015	0.6582	0.8870	0.6106
1.3158	1100	-	0.2266	0.2996	0.6576	0.8859	0.6097
1.4354	1200	-	0.2337	0.2944	0.6581	0.8863	0.6066
1.5550	1300	-	0.2343	0.2928	0.6572	0.8829	0.6064
1.6746	1400	-	0.2342	0.2920	0.6566	0.8822	0.6041
1.7943	1500	1.6345	0.2358	0.2947	0.6575	0.8824	0.6026
1.9139	1600	-	0.2357	0.2945	0.6576	0.8824	0.6029

Framework Versions

Python: 3.10.12
Sentence Transformers: 3.3.0
Transformers: 4.45.2
PyTorch: 2.5.1+cu124
Accelerate: 1.1.0
Datasets: 3.1.0
Tokenizers: 0.20.3

Citation

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

MultipleNegativesRankingLoss

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}