Biotech news dataset

This dataset is specifically curated to address the limitations of existing benchmarks by incorporating rich and complex content derived from the biotech news domain. It encompasses diverse biotech news articles consisting of various events, offering a more nuanced perspective on information extraction challenges.

A distinctive feature of this dataset is its emphasis on not only identifying the overarching theme but also extracting information about the target companies associated with the news. This dual-layered approach enhances the dataset's utility for applications that require a deeper understanding of the relationships between events, companies, and the biotech industry as a whole.

Classes

The dataset consists of 31 classes, including None values.

Category	Description
Alliance & Partnership	Forming an alliance or partnership.
Article Publication	Publishing an article.
Clinical Trial Sponsorship	Sponsoring or participating in a clinical trial.
Closing	Shutting down a facility/office/division or ceasing an initiative.
Company Description	Describing or profiling the company.
Department Establishment	Establishing a new department or division.
Event Organisation	Organizing or participating in an event.
Event Organization	Organizing or participating in an event like a conference, exhibition, etc.
Executive Appointment	Appointing a new executive.
Executive Statement	A statement or quote from an executive of a company.
Expanding Geography	Expanding into new geographical areas.
Expanding Industry	Expanding into new industries or markets.
Foundation	Establishing a new charitable foundation.
Funding Round	Raising a new round of funding.
Hiring	Announcing new hires or appointments at the company.
Investment in Public Company	Making an investment in a public company.
IPO Exit	Having an initial public offering or acquisition exit.
M&A	Mergers, acquisitions, or divestitures.
New Initiatives & Programs	Announcing new initiatives or programs.
New Initiatives or Programs	Announcing new initiatives, programs, or campaigns.
None	No label.
Participation in an Event	Participating in an industry event, conference, etc.
Partnerships & Alliances	Forming partnerships or strategic alliances with other companies.
Patent Publication	Publication of a new patent filing.
Product Launching & Presentation	Launching or unveiling a new product.
Product Updates	Announcing updates or new versions of existing products.
Regulatory Approval	Getting approval from regulatory bodies for products, services, trials, etc.
Service & Product Providing	Launching or expanding products or services.
Subsidiary Establishment	Establishing a new subsidiary company.
Support & Philanthropy	Philanthropic activities or donations.
Other	Other events that don't fit into defined categories.

Benchmark

We trained various models with binary-cross entropy loss and evaluated them on the test set.

Model	Accuracy	F1	Precision	Recall
DeBERTa-small	96.58	67.69	74.18	62.19
DeBERTa-base	96.60	67.55	74.81	61.58
DeBERTa-large	96.99	74.07	73.46	74.69
SciBERT-uncased	96.57	68.07	73.07	63.71
Flan-T5-base	96.85	71.10	75.71	67.07

Recommended reading:

• Check the general overview of the dataset on Medium - Finally, a decent multi-label classification benchmark is created: a prominent zero-shot dataset.
• Try to train your own model on the datset - Multi-Label Classification Model From Scratch: Step-by-Step Tutorial