|
--- |
|
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) |
|
|
|
| |
|
|
|
## Uses |
|
|
|
### Direct Use for Inference |
|
|
|
```python |
|
from span_marker import SpanMarkerModel |
|
from span_marker.tokenizer import SpanMarkerTokenizer |
|
|
|
|
|
# Download from the 🤗 Hub |
|
model = SpanMarkerModel.from_pretrained("lambdavi/span-marker-luke-legal") |
|
tokenizer = SpanMarkerTokenizer.from_pretrained("roberta-base", config=model.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 |
|
from span_marker.tokenizer import SpanMarkerTokenizer |
|
|
|
|
|
# Download from the 🤗 Hub |
|
model = SpanMarkerModel.from_pretrained("lambdavi/span-marker-luke-legal") |
|
tokenizer = SpanMarkerTokenizer.from_pretrained("roberta-base", config=model.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> |
|
|
|
<!-- |
|
### 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 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} |
|
} |
|
``` |
|
|
|
<!-- |
|
## Glossary |
|
|
|
*Clearly define terms in order to be accessible across audiences.* |
|
--> |
|
|
|
<!-- |
|
## Model Card Authors |
|
|
|
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.* |
|
--> |
|
|
|
<!-- |
|
## Model Card Contact |
|
|
|
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.* |
|
--> |
