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usman-yello/job-tagging-summary

sourceHugging Faceupdated 2y agoView on Hugging Face
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This model is a multilabel classifier that takes an input string containing position_title and summary of responsibilities, and returns job tags.

Model Details

Fine tuned bert-base-uncased for custom job tagging.

Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

  • —Developed by: [Usman Naveed]
  • —Model type: [Encoder|Text Classifier]
  • —Language(s) (NLP): [English]
  • —Finetuned from model [optional]: [bert-base-uncased]

Model Sources [optional]

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  • —Repository: [https://huggingface.co/google-bert/bert-base-uncased]

Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> This model is only intended to classify jobs into job tags.

Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. --> The dataset trained on was imbalanced, and contained more Engineering and Finance jobs than any other tag. This may cause bias towards Engineering and Finance tags.

[More Information Needed]

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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Dataset used to train this model: https://huggingface.co/datasets/usman-yello/job-tagging-with-summary

Preprocessing [optional]
  • —Remove HTML and markdown from the responsibilties
  • —Create a new text column which is the concatenation of the position_title and the responsibilities, use this column

Testing Data, Factors & Metrics

Testing Data

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[More Information Needed]

Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

[More Information Needed]

Metrics

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Results

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Summary