arnosimons
/

astro-hep-bert

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 pipeline_tag: feature-extraction
 ---
-# Model Card for Model ID
-Astro-HEP-BERT is a bidirectional transformer based on Google's ``bert-base-uncased'' and additionally trained on paragraphs from scholarly articles related to astrophysics and/or high-energy physics (HEP).
-The main intended use of the model is to produce contextualized word embeddings for studying epistemic change in astrophysics and high-energy physics.
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
 ## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-- **Developed by:** Arno Simons
-- **Funded by [optional]:** European Research Council (ERC) under Grant agreement ID: [101044932](https://doi.org/10.3030/101044932)
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** English
 - **License:** apache-2.0
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-The main intended use of the model is to produce contextualized word embeddings for studying epistemic change in astrophysics and high-energy physics.
 ## How to Get Started with the Model
 Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 **BibTeX:**
-[More Information Needed]
 **APA:**
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-## Model Card Authors [optional]
-[More Information Needed]

 pipeline_tag: feature-extraction
 ---
+# Model Card for **Astro-HEP-BERT**
+**Astro-HEP-BERT** is a bidirectional transformer designed primarily to generate contextualized word embeddings for analyzing epistemic change in astrophysics and high-energy physics. Built upon Google's "bert-base-uncased," the model underwent additional training for three epochs using approximately 21.5 million paragraphs extracted from around 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.
+For further insights into the model and the corpus, please refer to the Astro-HEP-BERT paper [link coming soon].
+<!-- <a href="" target="_blank">Astro-HEP-BERT paper</a>. -->
 ## Model Details
+- **Developer:** <a href="https://www.tu.berlin/en/hps-mod-sci/arno-simons" target="_blank">Arno Simons</a>
+- **Funded by:** European Research Council (ERC) under Grant agreement ID: <a href="https://doi.org/10.3030/101044932" target="_blank">101044932</a>
+- **Language (NLP):** English
 - **License:** apache-2.0
+- **Parent model:** Google's "<a href="https://huggingface.co/google-bert/bert-base-uncased" target="_blank">bert-base-uncased</a>"
+<!---
 ## How to Get Started with the Model
 Use the code below to get started with the model.
+[Coming soon]
+## Citation
 **BibTeX:**
+[Coming soon]
 **APA:**
+[Coming soon]
+-->