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jayant-yadav
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roberta-base-multinerd

Token Classification
Transformers
Safetensors
English
roberta
ner
named-entity-recognition
Eval Results
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roberta-base-multinerd / README.md
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metadata
license: apache-2.0
datasets:
  - Babelscape/multinerd
language:
  - en
metrics:
  - f1
pipeline_tag: token-classification
tags:
  - ner
  - named-entity-recognition
  - token-classification
model-index:
  - name: robert-base on MultiNERD by Jayant Yadav
    results:
      - task:
          type: token-classification
          name: Named Entity Recognition
        dataset:
          type: Babelscape/multinerd
          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
base_model: roberta-base

Model Card for Model ID

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Model Details

Model Description

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Uses

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

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

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Training Details

Training Data

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Training Procedure

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Training Hyperparameters

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Evaluation

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 [More Information Needed]

Compute Infrastructure

2x T4 GPUs [More Information Needed]

Hardware

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Software

Pytorch [More Information Needed]

Model Card Contact

(jayant-yadav)[https://huggingface.co/jayant-yadav] [More Information Needed]