Update README.md

README.md

@@ -6,6 +6,10 @@ datasets:
 - twitter_pos_vcb
 metrics:
 - accuracy
+- poseval
+- f1
+- recall
+- precision
 model-index:
 - name: bert-base-cased-finetuned-Stromberg_NLP_Twitter-PoS_v2
   results:
@@ -22,11 +26,11 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.9853480683735223
+language:
+- en
+pipeline_tag: token-classification
 ---
 
-<!-- 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-cased-finetuned-Stromberg_NLP_Twitter-PoS_v2
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the twitter_pos_vcb dataset.
@@ -83,15 +87,15 @@ It achieves the following results on the evaluation set:
 
 ## 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/Token%20Classification/Monolingual/StrombergNLP-Twitter_pos_vcb/NER%20Project%20Using%20StrombergNLP%20Twitter_pos_vcb%20Dataset%20with%20PosEval.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/strombergnlp/twitter_pos_vcb
 
 ## Training procedure
 
@@ -119,4 +123,4 @@ The following hyperparameters were used during training:
 - Transformers 4.28.1
 - Pytorch 2.0.0
 - Datasets 2.11.0
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3