Update README.md

README.md

@@ -24,24 +24,24 @@ datasets:
 - wikipedia
 - bookcorpus
 tags:
-- physics
+- arXiv
 - astrophysics
+- conceptual analysis
+- epistemic change
 - high-energy physics (HEP)
 - history of science
-- philosophy of science
+- semantic shift detection
 - sociology of science
+- philosophy of science
+- physics
 - word embeddings
-- semantic shift detection
-- conceptual change
-- epistemic change
-- arXiv
 ---
 
 # Model Card for Astro-HEP-BERT
 
 **Astro-HEP-BERT** is a bidirectional transformer designed primarily to generate contextualized word embeddings for computational conceptual analysis in astrophysics and high-energy physics (HEP). Built upon Google's `bert-base-uncased`, the model underwent additional training for three epochs using 21.84 million paragraphs found in more than 600,000 scholarly articles sourced from arXiv, all pertaining to astrophysics and/or high-energy physics (HEP). The sole training objective was masked language modeling.
 
-The Astro-HEP-BERT project embodies the spirit of a tabletop experiment or grassroots scientific effort. It exclusively utilized open-source inputs during training, and the entire training process was completed on a single MacBook Pro M2/96GB in 48 days for 3 epochs. This project stands as a proof of concept, showcasing the viability of employing a bidirectional transformer for research ventures in the history, philosophy, and sociology of science (HPSS) even with limited financial resources.
+The Astro-HEP-BERT project demonstrates the general feasibility of training a customized bidirectional transformer for computational conceptual analysis in the history, philosophy, and sociology of science as an open-source endeavor that does not require a substantial budget. Leveraging only freely available code, weights, and text inputs, the entire training process was conducted on a single MacBook Pro Laptop (M2/96GB).
 
 For further insights into the model, the corpus, and the underlying research project (<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.3030/101044932" >Network Epistemology in Practice</a>) please refer to the Astro-HEP-BERT paper [link coming soon].