README.md

---
license: apache-2.0
datasets:
- Babelscape/multinerd
language:
- en
metrics:
- f1
- precision
- recall
pipeline_tag: token-classification
tags:
- ner
- named-entity-recognition
- token-classification
model-index:
- name: robert-base on MultiNERD by Jayant Yadav
  results:
  - task:
      type: named-entity-recognition-ner
      name: Named Entity Recognition
    dataset:
      type: Babelscape/multinerd
      name: MultiNERD (English)
      split: test
      revision: 2814b78e7af4b5a1f1886fe7ad49632de4d9dd25
      config: Babelscape/multinerd
      args:
        split: train[:50%]
    metrics:
    - type: f1
      value: 0.943
      name: F1
    - type: precision
      value: 0.939
      name: Precision
    - type: recall
      value: 0.947
      name: Recall
      config: seqeval
    paper: https://aclanthology.org/2022.findings-naacl.60.pdf
base_model: roberta-base
library_name: transformers
---
# Model Card for Model ID

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This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).

## Model Details

### Model Description

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- **Developed by:** [More Information Needed]
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### Model Sources [optional]

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## Uses

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### Direct Use

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## Bias, Risks, and Limitations

Only trained on English split of MultiNERD dataset. Therefore will not perform well on other languages.
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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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### Training Procedure 

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#### Preprocessing [optional]

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#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data & Metrics

#### Testing Data

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#### Metrics

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### Results

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## Technical Specifications [optional]

### Model Architecture and Objective
Follows the same as RoBERTa-BASE
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### Compute Infrastructure
2x T4 GPUs
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#### Hardware

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#### Software
Pytorch
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## Model Card Contact
(jayant-yadav)[https://huggingface.co/jayant-yadav]
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