Create README.md

README.md

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+---
+license: mit
+datasets:
+- webis/Touche23-ValueEval
+language:
+- en
+metrics:
+- f1
+tags:
+- social-values
+---
+# Schwartz Value Classifier
+This classifier is intended to predict the existence of social values from text snippets.
+
+*Disclaimer: this is not the official repo published by the authors of the paper, and may not truly replicate the performance described in the original study* 
+
+## Value dimensions
+1. security
+2. power
+3. achievement
+4. hedonism
+5. stimulation
+6. self-direction
+7. universalism
+8. benevolence
+9. conformity
+10. tradition
+    
+## Datasets
+This model is finetuned on two datasets: ValueNet and Touche23-ValueEval
+We follow the original paper to convert both datasets into a binary classification task for each dimension.
+- ValueNet: a sentence has a positive label if the original label contains 1 (positive) or -1 (negative), and 0 if the original label is 0.
+- ValueEval: a sentence is assigned a positive label if the original label vector is marked 1 for that dimension. Since the original paper follows a 20-dimension refined categorization, we map them back to 10 dimensions. Therefore, the same sentence appears ten times, once for each dimension.
+
+## How to use
+Start your sentence with a label that indicates which dimension to measure. An example would be:
+
+- <power> [SEP] staying out late after telling my girlfriend I could be home early
+
+Please make sure to follow the exact format "<value\_name>" at the beginning of the sentence as this is a special token in the tokenizer: any spaces or different formats will not be encoded correctly.
+
+## Performances
+- F1 score (macro): 0.759
+
+## References
+Do Differences in Values Influence Disagreements in Online Discussions? (EMNLP'23) [link](https://aclanthology.org/2023.emnlp-main.992/)