Update README.md

README.md

@@ -5,29 +5,28 @@ widget:
 - text: "Ninna Gay is an exceptional photographer who has been exhibiting her work since 1996 in Ireland, Northern Ireland, and France. She is a dominant figure in the world of photography, and her photographs are a testament to her outstanding talent and forceful personality."
 ---
 
-# Model Card for Model ID
+# Language Agency Classifier
 
-<!-- Provide a quick summary of what the model is/does. -->
+The Language Agency Classifier was created by (Wan et al., 2023) and aims to classify sentences based on the level of agency expressed in each sentence. 
+Classifying sentence agency can help expose latent gender bias, where women may be 
+described with more communal (community-oriented) words and men may be described with more agentic (self/leadership-oriented) words.
 
-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).
+The Language Agency Classifier is implemented with a BERT model architecture given an 80/10/10 train/dev/test split.  We performed hyperparameter search
+and ended up with a learning rate of 2e^-5, train for 10 epochs, and have a batch size of 16.
 
-## Model Details
-
-The model was trained on the [Language Agency Classification Dataset](https://huggingface.co/datasets/elaine1wan/Language-Agency-Classification).
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
+In the dataset ([Language Agency Classifier Dataset](https://huggingface.co/datasets/elaine1wan/Language-Agency-Classification)), the initial biography is 
+sampled from the Bias in Bios dataset (De-Arteaga et al., 2019a), which is sourced from online biographies in the Common Crawl corpus. We prompt ChatGPT 
+to rephrase the initial briography into two versions: one leaning towards agentic language style and another leaning towards communal language style.
 
+An example usage is below.
 
+```
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained("emmatliu/language-agency-classifier")
+model = AutoModelForSequenceClassification.from_pretrained("emmatliu/language-agency-classifier")
+```
 
 ### Model Sources
 
@@ -37,16 +36,6 @@ The model was trained on the [Language Agency Classification Dataset](https://hu
 - **Paper:** ["Kelly is a Warm Person, Joseph is a Role Model"](https://arxiv.org/pdf/2310.09219.pdf)
 - **Demo:** [LLMReferenceLetterBias](https://huggingface.co/spaces/emmatliu/LLMReferenceLetterBias)
 
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
 ## Citation
 
 ```