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metadata
tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_student_name_detector
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.8311688312
          - name: NER Recall
            type: recall
            value: 0.8421052632
          - name: NER F Score
            type: f_score
            value: 0.8366013072
Feature Description
Name en_student_name_detector
Version 0.0.1
spaCy >=3.4.1,<3.5.0
Default Pipeline transformer, ner
Components transformer, ner
Sources longformer
License Apache 2.0
Author Langdon Holmes

Label Scheme

View label scheme (1 labels for 1 components)
Component Labels
ner STUDENT

Accuracy

Type Score
ENTS_F 83.66
ENTS_P 83.12
ENTS_R 84.21
TRANSFORMER_LOSS 56255026.35
NER_LOSS 31154.89

Training Data

6,293 student writing assignments were submitted as PDF files. All documents were reflection assignments in response to the same prompt in the same online course. Student names were labeled by human raters (one rater per document). A preliminary model was trained and all disagreements between this model and the human annotations were adjudicated by two additional reviewers. The training dataset includes all 6,293 documents, 845 of which include student names. There are 1,155 student name annotations in total.

To Use

This model has been packaged using spaCy. It is available as a huggingface model or a pip package. Performance of the model should be evaluated on in-domain data before deployment in production, particularly when confidential information is involved.