Update README.md

README.md

@@ -1,10 +1,11 @@
 ---
 tags:
 - generated_from_trainer
-datasets:
-- imagefolder
 metrics:
 - accuracy
+- f1
+- recall
+- precision
 model-index:
 - name: dit-base-Document_Classification-RVL_CDIP
   results:
@@ -21,14 +22,14 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.976678084687705
+language:
+- en
 ---
 
-<!-- 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. -->
-
 # dit-base-Document_Classification-RVL_CDIP
 
-This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on the imagefolder dataset.
+This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base).
+
 It achieves the following results on the evaluation set:
 - Loss: 0.0786
 - Accuracy: 0.9767
@@ -44,15 +45,15 @@ 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/Vision_Audio_and_Multimodal_Projects/blob/main/Document%20AI/Multiclass%20Classification/Document%20Classification%20-%20RVL-CDIP/Document%20Classification%20-%20RVL-CDIP.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/achrafbribiche/document-classification
 
 ## Training procedure
 
@@ -84,4 +85,4 @@ 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