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---
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:29992
- loss:CosineSimilarityLoss
widget:
- source_sentence: What did the Court direct the State Government to do?
  sentences:
  - In the consolidated proceeding therefore the tribunal had to decide firstly whether
    the bunga was the property of the Golden Temple. If it decided that, all the claims
    would necessarily fall 338 through. But if it held that the bunga was not the
    property of the Golden Temple it had to adjudicate on the respective claims of
    Jaswant Singh, Kesar Singh and Balwant Singh. By majority, the tribunal held that
    the bunga was not the property of the Golden Temple. It therefore had to decide
    to which of the three claimants under section 5, if any, the bunga could be held
    to belong. It negatived the claims of Kesar Singh and Jaswant Singh. As to Balwant
    Singh 's claim it held by a majority that Balwant Singh had no personal or private
    right in the bunga. It further held that the bunga was wakf property dedicated
    to the pilgrims to the Golden Temple and that the descendants of Maharaja Sher
    Singh were the managers of the bunga.
  - The second meeting was held on the 29th March, 1952, and the third on the 14th
    of June, 1952. The expert member was not present at any other meeting except the
    first and on the 27th of 741 May, 1952, he wrote a letter to the Chief Commissioner
    stating that he was proceeding to Europe on the 3rdd June, 1952, for a period
    of three months.
  - It is necessary to mention in this connection that on September 21, 1984 this
    Court while granting special leave made an order of stay of operation of the High
    Court judgment pending hearing of the appeal. But subsequently on March 18, 1986
    after hearing the learned counsels the interim order of stay was recalled in consideration
    of the fact that U.P. Public Service Commission had already cancelled the candidature
    of the appellant and withdrawn the recommendation made in his favour for the reason
    inter alia that he lacked in five years experience in Drug testing. This Court
    also directed the State Government to appoint a member or one Indian Administrative
    Service to function as the Food & Drug Controller, U.P. PG NO 42 It has been urged
    on behalf of the appellant, Dr. Bindal that the order of the Public Service Commission
    in cancelling the candidature of the appellant and withdrawing the recommendation
    made in his favour is wholly illegal and bad in as much as the Government has
    considered the certificates produced by the appellant and found that the appellant
    had the requisite experience of five years in Drug testing and as such he was
    appointed by the Government as Food and Drug Controller, U.P.
- source_sentence: What power does Article 11 grant to Parliament?
  sentences:
  - Civil Appeal Nos. 1742 1743 of 1969. Appeals by Special Leave from the Judgment
    and order dated 12 12 1968 of the Allahabad High Court in R.S.A. No. 2777 of 1972.
    section N. Andley, Uma Datta and T. C. Sharma for the Appellant in CA 1742/69.
    A. P. section Chauhan and N. N. Sharma for Respondent No. 1 in CA 1742/69 and
    for the Appellant in CA 1743/69. 1000 The Judgment of the Court was delivered
    by KOSHAL, J.
  - There is, therefore, a clear averment in the plaint that an equitable mortgage
    was created on May 10, 1947, and that was acknowledged by the agreement dated
    July 5, 1947. The 1st defendant did not file any written statement denying the
    said allegations.
  - In Raja Kulkarni and Ors. vs State of Bombay(1), one of the contentious canvassed
    before the Constitution Bench was that Sec. 13 of the Bombay Industrial Relations
    Act, 1946 as it then stood provided that a union can be registered as a representative
    union for an industry in a local area if it has for the whole of the period of
    three months next preceding the date of its application, a membership of not less
    than 15% of the total number of employees employed in any F industry in any local
    area. If the union does not satisfy that condition and has a membership of not
    less than 5%, it could be registered as a qualified union Rashtriya Mill Mazdoor
    Sangh was registered as a representative union while the Mill Mazdoor Sabha was
    registered as a qualified union. It was contended on behalf to Mill Mazdoor Sabha
    of which the appellants before this Court were the office bearers that the provisions
    that conferred an exclusive right only on the representative union to represent
    workmen was violative of fundamental freedoms guaranted to the members of Mill
    Mazdoor Sabha . (1) [1954] SCR 384. 508 or any other workman who is not a member
    of the representative union under article 19 (1) (a) and (c) and was also violative
    of article 14 inasmuch as the two representatives of workmen were denied equality
    before law or the equal protection of laws. The Constitution Bench repelled the
    contention observing that such a provision does no t deny either the fundamental
    freedom of speech and expression or the right to form association. The Court said
    that it is always open to the workmen who are not members of the representative
    union to form their own association or union and to claim higher percentage of
    membership so as to dethrone the representative union and take its place. This
    decision should have concluded the matter.
- source_sentence: What is the only course open for the Government in these circumstances?
  sentences:
  - This definition is undoubtedly relevant in dealing with the question of continuous
    service by reference to the provisions of Industrial Disputes ' Act but its operation
    cannot be automatically extended in dealing with an interpretation of the words
    "continuous service" in an award made in an industrial dispute unless the context
    in which the expression is used in the award justifies it. In other words, the
    expression "continuous service" may be statutorily defined in which case the definition
    will prevail. An award using the said expression may itself give a definition
    of that expression and that will bind parties in dealing with claims arising from
    the award. Where, however, the award does not explain the said expression and
    statutory definitions contained in other Acts are of no material assistance it
    would be necessary to examine the question on principle and decide what the expression
    should mean in any given award '; and that is precisely what the tribunal had
    to do in the present case.
  - Before the enactment of section 289(2) if it disagreed with the finding, it could
    reject the proceeding on the ground that the matter was cognizable by the other
    court, As neither court was bound by the finding of the other, the litigant could
    not get relief in any forum. Section 289(2) has been specially enacted to avoid
    such a deadlock. In such a situation, section 289(2) compels the court to refer
    the matter to the High Court and to obtain a Provisions corresponding to sections
    290, 291 and 289(1) were contained in sections 124 A, 124B, 124C and 124D of the
    Oudh Rent Act 1886 and sections 268, 269 and 267(1) of the Agra Tenancy Act, 1926.
  - 'Sub section (1) of section 125 Cr. P.C. provides as under: "If any person having.
    sufficient means ne glects or refuses to maintain (a) his wife, unable to maintain
    herself or (b) his legitimate or illegitimate minor child, whether married or
    not, unable to maintain itself, or (c) his legitimate or illegitimate child (not
    being a married daughter) who has at tained majority, where such child is, by
    reason of any physical or mental abnormality or injury unable to maintain itself,
    or (d) his father or mother, unable to maintain himself or herself, a Magistrate
    of the first class may, upon proof of such neglect or refusal, order such person
    to make a monthly allowance for the maintenance of his wife or such child, father
    or mother, at such monthly rate not exceeding five hundred rupees in the whole,
    as such Magistrate thinks fit, and to pay the same to such person as the Magistrate
    may from time to time direct: Provided that the Magistrate may order the father
    of a minor female child referred to in clause (b) to make such allow ance, until
    she attains her majority, if the Magistrate is satisfied that the husband of such
    minor female child, if married, is not possessed of sufficient means. "'
- source_sentence: What decision did these cases follow?
  sentences:
  - Samples of the seized illicit liquor were sent to the Chemical Analyst whose report,
    dated 10th of January 1991, indicated that the samples contained ethyl alcohol
    34% v/v in water.
  - In that view of the matter the Trial Court held that the respondent was not entitled
    to the protec tion of the Bombay Rent Act conferred on a licensee by Maharashtra
    Act 17 of 1973. The Court allowed the appel lants ' application and made an order
    under section 43 of the S.C.C. Act directing the respondent to vacate and hand
    over peaceful possession of the premises to the appellants within one month from
    the date of the order i.e. the 11th Octo ber, 1974. This order was not appealable.
    Hence respondent filed a revision before the High Court.
  - 'Next, we come to Shyam Lal. His alienations were as follows: 19 6 97 Mortgage.
    Shops in Sanbhal. Owner. exhibit W 1(C.A. 94) 9 11 07 do House in Sambhal. No
    recital exhibit TT 1(C.A. 94) 17 9 09 do Bilalpat. do exhibit UU 1 (C. A. 94)
    In addition, he made the following transfers jointly with his brother Pyare Lal:
    18 1 06 Mortgage. Bilalpat & shops No recitals. exhibit EEE 1 in Sambhal. (C.A.94)
    21 2 10 do Bilalpat & Sabz. do exhibit AA 1(C.A 94) Pyare Lal also made two transfers
    on his own 23 9 18 Sale Bilalpat. "Devolved on exhibit 15(C.A. 94) me"from Nanak
    Chand by right of inheritance. 2 1 20 do do do exhibit 18 (C. A. 93) Lastly, there
    is Bhukban Saran, who is Maha Devi ''s daughter ''s son. He transferred as follows:
    26 3 18 SaleHouses, etc.in Absoluteand Sambhal. exclusive exhibit MM 1 (C.A.92)
    owner. 9 1 21 Relinquish Bilalpat do exhibit DD 1 (C.A. 93) ment.'
- source_sentence: What entry is mentioned in relation to tax on land?
  sentences:
  - Now it is true that the so called will of 1864 does not make provision for the
    grandsons, nor does it expressly confer an absolute estate on the legatees, but
    the witness is illiterate and had to depend on what he was told about the contents
    and meaning of the document, and what we have to test is the truth of his assertion
    that the plaintiff Mukand Ram and Kanhaiya Lal, and other members of the family,
    told him that Mst. Pato had given the property to her daughters and grandsons.
    If they told him this, as he says they did, then it operates as an admission against
    Mukand Ram and shifts the burden of proof to him because he was one of the persons
    who made the statement. The statements made by the others are not relevant except
    in so far as they prove the conduct of the family. The plaintiff (P.W. 11 in C.A.
    91/50) admits that Mst. Pato divided the estate but says that it was only for
    convenience of management and that neither she nor her daughters had, or pretended
    to have, anything more than a life estate. He denies that there was any gift or
    family arrangement. But he had to admit that the grandsons also got properties
    at the same time. His explanation is that it was for the purposes of "shradh"
    and pilgrimage to Gaya and he says that though they were given possession they
    were not the "owners".
  - This Court rejected ' that submission and held that after vesting of all the rights
    mentioned in. section 6 of the Act in the State of Uttar Pradesh, new bhumidhari
    rights came into existence under section 18 of the Act.
  - 'In that connection, the following observations lay down the guide lines: "It
    is well settled that the entries in the three legislative lists have to be interpreted
    in their widest amplitude and there fore if a tax can reasonably be held to be
    a tax on land it will come within entry 49. Further it is equally well settled
    that tax on land may be based on the annual value of the land and would still
    be a tax on land and would not be beyond the com petence of the State legislature
    on the ground that it is a tax on income: (See Ralla Ram vs The province of East
    Punjab: It follows therefore that the use to which the land is put can be taken
    into account in imposing a tax (1) ; (2)Quoted in Liberty cinema: P. 484. 339
    on it within the meaning of entry 49 of List II, for the annual value of land
    which can certainly be taken into account in imposing a tax for the purpose of
    this entry would necessarily depend upon the use to which the land is put." (p.
    49).'
pipeline_tag: sentence-similarity
library_name: sentence-transformers
---

# SentenceTransformer

This is a [sentence-transformers](https://www.SBERT.net) model trained. 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:** [Unknown](https://huggingface.co/unknown) -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 dimensions
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->

### Model Sources

- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)

### Full Model Architecture

```
SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (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})
)
```

## Usage

### Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

```bash
pip install -U sentence-transformers
```

Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("rossieRuby/nyayadrishti-bert-v2")
# Run inference
sentences = [
    'What entry is mentioned in relation to tax on land?',
    'In that connection, the following observations lay down the guide lines: "It is well settled that the entries in the three legislative lists have to be interpreted in their widest amplitude and there fore if a tax can reasonably be held to be a tax on land it will come within entry 49. Further it is equally well settled that tax on land may be based on the annual value of the land and would still be a tax on land and would not be beyond the com petence of the State legislature on the ground that it is a tax on income: (See Ralla Ram vs The province of East Punjab: It follows therefore that the use to which the land is put can be taken into account in imposing a tax (1) ; (2)Quoted in Liberty cinema: P. 484. 339 on it within the meaning of entry 49 of List II, for the annual value of land which can certainly be taken into account in imposing a tax for the purpose of this entry would necessarily depend upon the use to which the land is put." (p. 49).',
    'Now it is true that the so called will of 1864 does not make provision for the grandsons, nor does it expressly confer an absolute estate on the legatees, but the witness is illiterate and had to depend on what he was told about the contents and meaning of the document, and what we have to test is the truth of his assertion that the plaintiff Mukand Ram and Kanhaiya Lal, and other members of the family, told him that Mst. Pato had given the property to her daughters and grandsons. If they told him this, as he says they did, then it operates as an admission against Mukand Ram and shifts the burden of proof to him because he was one of the persons who made the statement. The statements made by the others are not relevant except in so far as they prove the conduct of the family. The plaintiff (P.W. 11 in C.A. 91/50) admits that Mst. Pato divided the estate but says that it was only for convenience of management and that neither she nor her daughters had, or pretended to have, anything more than a life estate. He denies that there was any gift or family arrangement. But he had to admit that the grandsons also got properties at the same time. His explanation is that it was for the purposes of "shradh" and pilgrimage to Gaya and he says that though they were given possession they were not the "owners".',
]
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]
```

<!--
### Direct Usage (Transformers)

<details><summary>Click to see the direct usage in Transformers</summary>

</details>
-->

<!--
### Downstream Usage (Sentence Transformers)

You can finetune this model on your own dataset.

<details><summary>Click to expand</summary>

</details>
-->

<!--
### Out-of-Scope Use

*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->

<!--
## Bias, Risks and Limitations

*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->

<!--
### Recommendations

*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->

## Training Details

### Training Dataset

#### Unnamed Dataset

* Size: 29,992 training samples
* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>label</code>
* Approximate statistics based on the first 1000 samples:
  |         | sentence_0                                                                        | sentence_1                                                                           | label                                                          |
  |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:---------------------------------------------------------------|
  | type    | string                                                                            | string                                                                               | float                                                          |
  | details | <ul><li>min: 7 tokens</li><li>mean: 15.09 tokens</li><li>max: 45 tokens</li></ul> | <ul><li>min: 10 tokens</li><li>mean: 153.59 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.48</li><li>max: 1.0</li></ul> |
* Samples:
  | sentence_0                                                              | sentence_1                                                                                                                                                                                                                                                                                                                                                                                                                                            | label            |
  |:------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
  | <code>Why did the respondents dispute the demurrage charges?</code>     | <code>The respondents disputed the right of the Port Trust to charge any demurrage for the period during which the goods were detained by the Customs authorities for analytical test. as well as for the Import Trade Control formalities.</code>                                                                                                                                                                                                    | <code>1.0</code> |
  | <code>What was the paid up capital of the subsidiary Company?</code>    | <code>The paid up capital of the subsidiary Company was Rs. 7,91,100 divided into 7,911 shares of Rs. 100 each.</code>                                                                                                                                                                                                                                                                                                                                | <code>1.0</code> |
  | <code>How many parts does the schedule attached to the Act have?</code> | <code>The schedule attached to the Act specifies, under two parts, the employments in respect of which the minimum wages of the employees can be fixed; and section 27 authorises the "appropriate Government", after giving three months ' notice of its intention to do so, to add to either part of the schedule, any other employment, in respect of which it is of the opinion that minimum rates of wages should be fixed under the Act.</code> | <code>1.0</code> |
* Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
  ```json
  {
      "loss_fct": "torch.nn.modules.loss.MSELoss"
  }
  ```

### Training Hyperparameters
#### Non-Default Hyperparameters

- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `num_train_epochs`: 1
- `multi_dataset_batch_sampler`: round_robin

#### All Hyperparameters
<details><summary>Click to expand</summary>

- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: no
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 16
- `per_device_eval_batch_size`: 16
- `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`: 5e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1
- `num_train_epochs`: 1
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.0
- `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`: False
- `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}
- `tp_size`: 0
- `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`: None
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `include_for_metrics`: []
- `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
- `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
- `average_tokens_across_devices`: False
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: round_robin

</details>

### Training Logs
| Epoch  | Step | Training Loss |
|:------:|:----:|:-------------:|
| 0.2667 | 500  | 0.2532        |
| 0.5333 | 1000 | 0.2527        |
| 0.8    | 1500 | 0.2524        |


### Framework Versions
- Python: 3.11.12
- Sentence Transformers: 4.1.0
- Transformers: 4.51.3
- PyTorch: 2.6.0+cu124
- Accelerate: 1.6.0
- Datasets: 2.14.4
- Tokenizers: 0.21.1

## Citation

### BibTeX

#### Sentence Transformers
```bibtex
@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",
}
```

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