Update README.md

README.md

@@ -6,6 +6,9 @@ tags:
 model-index:
 - name: apricot_clustering_coqa_deberta-v3-base_for_gpt-3.5-turbo-0125
   results: []
+datasets:
+- stanfordnlp/coqa
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -13,11 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # apricot_clustering_coqa_deberta-v3-base_for_gpt-3.5-turbo-0125
 
-This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the stanfordnlp/coqa dataset.
+This model is fine-tuned for black-box LLM calibration as part of the 🍑 Apricot paper ["Calibrating Large Language Models Using Their Generations Only"](https://arxiv.org/abs/2403.05973) (ACL 2024).
 
 ## Model description
 
-More information needed
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) to predict the calibration score for the gpt-3.5-turbo-0125 model on the questions from the stanfordnlp/coqa dataset. It uses the clustering type of calibration target score.
+
 
 ## Intended uses & limitations
 
@@ -45,4 +49,4 @@ The following hyperparameters were used during training:
 - Transformers 4.32.0
 - Pytorch 2.0.0+cu117
 - Datasets 2.14.6
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3