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README.md
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A benchmark for one narrow task: reading a real job posting and filling 11 structured fields. Job Opportunities API (JOA) built it to choose and train its own extraction models. This repository holds the results for 84 models (68 open-weight models, 13 quantised variants and JOA's 3 fine-tuned models), the per-field scores, the grading method and the reference labels for the listings we are allowed to share (221 of the 250).
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## The task
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Each model receives the text of one job posting, as stored by JOA, plus any structured data found on the page, and must return 11 fields:
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A benchmark for one narrow task: reading a real job posting and filling 11 structured fields. Job Opportunities API (JOA) built it to choose and train its own extraction models. This repository holds the results for 84 models (68 open-weight models, 13 quantised variants and JOA's 3 fine-tuned models), the per-field scores, the grading method and the reference labels for the listings we are allowed to share (221 of the 250).
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Article: https://dev.to/lucagiftzek/teaching-small-models-to-read-job-postings-our-arena-and-the-joa-small-advance-and-deep-fine-tunes-3hpb
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## The task
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Each model receives the text of one job posting, as stored by JOA, plus any structured data found on the page, and must return 11 fields:
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