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README.md
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---
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base_model: jjzha/jobbert-base-cased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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model-index:
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- name: results
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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## Model description
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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## Training procedure
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### Training hyperparameters
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---
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base_model: jjzha/jobbert-base-cased
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metrics:
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- accuracy
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- precision
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model-index:
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- name: results
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results: []
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widget:
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- text: You should be a skilled communicator.
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- text: You can programme in Python and CSS.
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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## Model description
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The base model (`jjzha/jobbert-base-cased`) is a BERT transformer model, pretrained on a corpus of ~3.2 million sentences from job adverts for the objective of Masked Language Modelling (MLM). A token classification head is added to the top of the model to predict a label for every token in a given spequence. In this instance, it is predicting a label for every token in a job description, where the label is either a 'B-SKILL', 'I-SKILL' or 'O' (not a skill).
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## Training and evaluation data
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The model was trained on 4112 job advert sentences.
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### Training hyperparameters
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