---
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: multinerd-a-multilingual-multi-genre-and-fine
    #   name: MultiNERD
    #   split: test
    #   revision: 2814b78e7af4b5a1f1886fe7ad49632de4d9dd25
    metrics:
    - type: f1
      value: 0.943
      name: F1
    - type: precision
      value: 0.939
      name: Precision
    - type: recall
      value: 0.947
      name: Recall
    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

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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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## Training Details

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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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