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---
library_name: span-marker
tags:
- span-marker
- token-classification
- ner
- named-entity-recognition
- generated_from_span_marker_trainer
- legal
metrics:
- precision
- recall
- f1
widget:
- text: >-
The seven-judge Constitution Bench of the Supreme Court in SBP and Co.
(supra) while reversing earlier five-judge Constitution Bench judgment in
Konkan Railway Corpn. Ltd. vs. Rani Construction (P) Ltd., (2002) 2 SCC 388
held that the power exercised by the Chief Justice of the High Court or the
Chief justice of India under Section 11(6) of the Arbitration Act is not an
administrative power but is a judicial power.
- text: >-
In The High Court Of Judicature At Patna Criminal Writ Jurisdiction Case
No.160 of 2021 Arising Out of Ps. Case No.-58 Year-2020 Thana- Bakhari
District- Begusarai ======================================================
Hanif Ur Rahman, son of Azhar Rahman, Resident of C-39, East Nizamuddin, New
Delhi....... Petitioner Versus 1. The State of Bihar (through Chief
Secretary, Govt. of Bihar) Main Secretariat, Patna - 800015. 2. Meena
Khatoon, wife of Mastan @ Noor Mohammad, Resident of Village- Mansurpur
Chaksikandar, P.S.- Bidupur, District- Vaishali (Bihar) 3. The Bihar Police,
through Standing Counsel. 4. Child Welfare Committee, through Chairperson,
Chanakyanagar, Mahmadpur, Begusarai. 5. The Superintendent, Alpawas Grih,
Nirala Nagar, Behind G.D. College, Ratanpur, Begusarai....... Respondents
====================================================== Appearance:For the
Petitioner:Ms. Kriti Awasthi, Advocate Mr. Sambhav Gupta, Advocate Mr.
Navnit Kumar, Advocate Mr. Shyam Kumar, Advocate For the
Respondents:Mr.Nadim Seraj, G.P.5 For the Resp. No. 2:Ms. Archana Sinha,
Advocate For the Resp. No. 4:Mr. Prabhu Narain Sharma, Advocate
====================================================== Coram: Honourable Mr.
Justice Rajeev Ranjan Prasad C.A.V. Judgment
- text: >-
1 R In The High Court Of Karnataka At Bengaluru Dated This The 19Th Day Of
February, 2021 Before The Hon'Ble Mr. Justice H.P. Sandesh Criminal Appeal
No.176/2011 Between: Sri G.L. Jagadish, S/O Sri G.N. Lingappa, Aged About 52
Years, Residing At No.29, 3Rd Main, Basaveshwara Housing Society Layout,
Vijayanagar, Near Bts Depot, Bengaluru-40....Appellant [By Sri H.
Ramachandra, Advocate For Sri H.R. Anantha Krishna Murthy And Associates -
(Through V.C.)] And: Smt. Vasantha Kokila, W/O Late N.R. Somashekhar, Aged
About 58 Years, Residing At No.322, 8Th Main, 3Rd Stage, 4Th Block,
Basaveshwaranagar, Bengaluru....Respondent [By Sri K.R. Lakshminarayana Rao,
Advocate] This Criminal Appeal Is Filed Under Section 378(4) Of Cr.P.C.
Praying To Set Aside The Order Dated 06.07.2010 Passed By The P.O. Ftc-Ii,
Bengaluru In Crl.A. No.470/2009 And Confirming The Order Dated 27.05.2009
Passed By The Xxii Acmm And Xxiv Ascj, Bengaluru In C.C.No.17229/2004
Convicting The Respondent/Accused For The Offence Punishable Under Section
138 Of Ni Act. 2 This Criminal Appeal Having Been Heard And Reserved For
Orders On 06.02.2021 This Day, The Court Pronounced The Following: Judgment
- text: >-
The petition was filed through Sh. Vijay Pahwa, General Power of Attorney
and it was asserted in the petition under Section 13-B of the Rent Act that
1 of 23 50% share of the demised premises had been purchased by the landlord
from Sh. Vinod Malhotra vide sale deed No.4226 registered on 20.12.2007 with
Sub Registrar, Chandigarh.
- text: >-
Mr. Arun Bharadwaj, ld. CGSC, appearing for the Union of India, has
Signature Not Verified Digitally Signed By:PRATHIBA M SINGH Signing
Date:09.10.2020 16:15 Digitally Signed By:SINDHU KRISHNAKUMAR Signing
Date:09.10.2020 16:50:02 reiterated the submissions made by Dr. Singhvi and
has further submitted that this petition ought to be heard with the OA No.
291/138/2020 pending before the CAT.
pipeline_tag: token-classification
model-index:
- name: SpanMarker
results:
- task:
type: token-classification
name: Named Entity Recognition
dataset:
name: legal_ner
type: unknown
split: eval
metrics:
- type: f1
value: 0.9099756690997567
name: F1
- type: precision
value: 0.9089703932832524
name: Precision
- type: recall
value: 0.9109831709477414
name: Recall
---
# SpanMarker
This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be used for Named Entity Recognition. It was trained on the Legal NER Indian Justice dataset.
## Model Details
### Model Description
- **Model Type:** SpanMarker
<!-- - **Encoder:** [Unknown](https://huggingface.co/unknown) -->
- **Maximum Sequence Length:** 128 tokens
- **Maximum Entity Length:** 6 words
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### Model Sources
- **Repository:** [SpanMarker on GitHub](https://github.com/tomaarsen/SpanMarkerNER)
- **Thesis:** [SpanMarker For Named Entity Recognition](https://raw.githubusercontent.com/tomaarsen/SpanMarkerNER/main/thesis.pdf)
### Model Labels
| Label | Examples |
|:-------------|:------------------------------------------------------------------------------------------------------------------------------------|
| CASE_NUMBER | "Section 80", "Section 66 (1)", "Section 26-A" |
| COURT | "(1962) 45 ITR 210 (SC)", "Writ Appeal No. 479 of 2005.", "CMA No. 6727 of 93" |
| DATE | "A. SHANKAR NARAYANA", "B.N. Srikrishna,", "(Jarat" |
| GPE | "Hongkong Bank", "HDFC Bank, Noida,", "Rahul & Co." |
| JUDGE | "Chandigarh", "UP", "Lakhaya," |
| LAWYER | "the", "Vijay Mishra", "Chandregowda" |
| ORG | "The", "A. Sandeep", "For" |
| OTHER_PERSON | "Indian Income-tax Act", "POTA", "Indian Income-tax Act, 1922," |
| PETITIONER | "Supreme Court.", "Supreme Court,", "Sessions Judge Jaipur City," |
| PRECEDENT | "C.C. Alavi Hazi Vs.Palapetty Mohd. & Anr", "Susamma Thomas, 1994 ACJ 1 (SC),", "United India Insurance Co. Ltd. v. Rajendra Singh" |
| PROVISION | "Jagdish Prasad Sharma,", "Bhanwarial,", "Amarsingh," |
| RESPONDENT | "19.8.1998", "28 March, 1959,", "29.4.1968," |
| STATUTE | "Kaur,", "Tarlochan Singh.", "Agya" |
| WITNESS | "Manju", "Sameer.", "Abid @ Guddu" |
## Uses
### Direct Use for Inference
```python
from span_marker import SpanMarkerModel, SpanMarkerTokenizer
# Download from the 🤗 Hub
model = SpanMarkerModel.from_pretrained("lambdavi/span-marker-luke-legal")
tokenizer = SpanMarkerTokenizer.from_pretrained("roberta-base", config=model.tokenizer.config)
model.set_tokenizer(tokenizer)
# Run inference
entities = model.predict("The petition was filed through Sh. Vijay Pahwa, General Power of Attorney and it was asserted in the petition under Section 13-B of the Rent Act that 1 of 23 50% share of the demised premises had been purchased by the landlord from Sh. Vinod Malhotra vide sale deed No.4226 registered on 20.12.2007 with Sub Registrar, Chandigarh.")
```
### Downstream Use
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
```python
from span_marker import SpanMarkerModel, Trainer, SpanMarkerTokenizer
# Download from the 🤗 Hub
model = SpanMarkerModel.from_pretrained("lambdavi/span-marker-luke-legal")
tokenizer = SpanMarkerTokenizer.from_pretrained("roberta-base", config=model.tokenizer.config)
model.set_tokenizer(tokenizer)
# Specify a Dataset with "tokens" and "ner_tag" columns
dataset = load_dataset("conll2003") # For example CoNLL2003
# Initialize a Trainer using the pretrained model & dataset
trainer = Trainer(
model=model,
train_dataset=dataset["train"],
eval_dataset=dataset["validation"],
)
trainer.train()
trainer.save_model("lambdavi/span-marker-luke-legal-finetuned")
```
</details>
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## Training Details
### Training Set Metrics
| Training set | Min | Median | Max |
|:----------------------|:----|:--------|:-----|
| Sentence length | 3 | 44.5113 | 2795 |
| Entities per sentence | 0 | 2.7232 | 68 |
### Training Hyperparameters
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5
### Training Results
| Epoch | Step | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy |
|:------:|:----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|
| 0.9997 | 1837 | 0.0137 | 0.7773 | 0.7994 | 0.7882 | 0.9577 |
| 2.0 | 3675 | 0.0090 | 0.8751 | 0.8348 | 0.8545 | 0.9697 |
| 2.9997 | 5512 | 0.0077 | 0.8777 | 0.8959 | 0.8867 | 0.9770 |
| 4.0 | 7350 | 0.0061 | 0.8941 | 0.9083 | 0.9011 | 0.9811 |
| 4.9986 | 9185 | 0.0064 | 0.9090 | 0.9110 | 0.9100 | 0.9824 |
| Metric | Value |
|:----------------------|:-------|
| f1-exact | 0.9237 |
| f1-strict | 0.9100 |
| f1-partial | 0.9365 |
| f1-type-match | 0.9277 |
### Framework Versions
- Python: 3.10.12
- SpanMarker: 1.5.0
- Transformers: 4.36.0
- PyTorch: 2.0.0
- Datasets: 2.17.1
- Tokenizers: 0.15.0
## Citation
### BibTeX
```
@software{Aarsen_SpanMarker,
author = {Aarsen, Tom},
license = {Apache-2.0},
title = {{SpanMarker for Named Entity Recognition}},
url = {https://github.com/tomaarsen/SpanMarkerNER}
}
```
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