Update README.md

README.md

@@ -3,34 +3,38 @@ license: apache-2.0
 base_model: bert-base-uncased
 tags:
 - generated_from_trainer
+- multiple_choice
 metrics:
 - accuracy
 model-index:
 - name: bert-base-uncased-Vitamin_C_Fact_Verification
   results: []
+datasets:
+- tasksource/bigbench
+language:
+- en
+pipeline_tag: question-answering
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # bert-base-uncased-Vitamin_C_Fact_Verification
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased).
+
 It achieves the following results on the evaluation set:
 - Loss: 0.6329
 - Accuracy: 0.7240
 
 ## Model description
 
-More information needed
+For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Multiple%20Choice/Vitamin%20C%20Fact%20Verification/Vitamin_C_Fact_Verification_Multiple_Choice_Using_BERT.ipynb
 
 ## Intended uses & limitations
 
-More information needed
+This model is intended to demonstrate my ability to solve a complex problem using technology.
 
 ## Training and evaluation data
 
-More information needed
+Dataset Source: https://huggingface.co/datasets/tasksource/bigbench/viewer/vitaminc_fact_verification
 
 ## Training procedure
 
@@ -58,4 +62,4 @@ The following hyperparameters were used during training:
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.2
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3