Update README.md

README.md

@@ -10,11 +10,9 @@ metrics:
 model-index:
 - name: canine-c-Mental_Health_Classification
   results: []
+pipeline_tag: text-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. -->
-
 # canine-c-Mental_Health_Classification
 
 This model is a fine-tuned version of [google/canine-c](https://huggingface.co/google/canine-c) on the None dataset.
@@ -27,15 +25,17 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This is a binary text classification model to distinguish between text that indicate potential mental health issue or not.
+
+For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Binary%20Classification/Mental%20Health%20Classification/CANINE%20-%20Mental%20Health%20Classification.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/reihanenamdari/mental-health-corpus
 
 ## Training procedure
 
@@ -57,10 +57,9 @@ The following hyperparameters were used during training:
 | 0.3429        | 1.0   | 1101 | 0.2640          | 0.9037   | 0.8804 | 0.8258 | 0.9426    |
 | 0.1923        | 2.0   | 2202 | 0.2419          | 0.9226   | 0.9096 | 0.9079 | 0.9113    |
 
-
 ### Framework versions
 
 - Transformers 4.26.1
 - Pytorch 1.12.1
 - Datasets 2.8.0
-- Tokenizers 0.12.1
+- Tokenizers 0.12.1