Update README.md

README.md

@@ -5,28 +5,31 @@ tags:
 model-index:
 - name: bert-base-uncased-Masked_Language_Model-US_Economic_News_Articles
   results: []
+language:
+- en
+metrics:
+- perplexity
 ---
 
-<!-- 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-Masked_Language_Model-US_Economic_News_Articles
 
-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: 1.8322
 
 ## Model description
 
-More information needed
+This is a masked language modeling project.
+
+For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Masked%20Language%20Model/US%20Economic%20News%20Articles/US_Economic_News_Articles_MLM.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://www.kaggle.com/datasets/trikialaaa/2k-clean-medical-articles-medicalnewstoday
 
 ## Training procedure
 
@@ -49,10 +52,11 @@ The following hyperparameters were used during training:
 | 2.004         | 2.0   | 4032 | 1.9002          |
 | 1.941         | 3.0   | 6048 | 1.8600          |
 
+Perplexity: 6.25
 
 ### Framework versions
 
 - Transformers 4.27.1
 - Pytorch 1.13.1+cu116
 - Datasets 2.10.1
-- Tokenizers 0.13.2
+- Tokenizers 0.13.2