Updating Information About Dataset & Project

README.md

@@ -6,6 +6,9 @@ datasets:
 - imagefolder
 metrics:
 - accuracy
+- f1
+- recall
+- precision
 model-index:
 - name: deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification
   results:
@@ -22,14 +25,15 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.8045685279187818
+language:
+- en
+pipeline_tag: image-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. -->
-
 # deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification
 
-This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
+This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224).
+
 It achieves the following results on the evaluation set:
 - Loss: 1.8587
 - Accuracy: 0.8046
@@ -53,7 +57,11 @@ More information needed
 
 ## Training and evaluation data
 
-More information needed
+<div>
+    <a href="https://www.kaggle.com/datasets/sartajbhuvaji/brain-tumor-classification-mri" span="">
+        Brain Tumor Image Classification Dataset
+    </a>
+</div>
 
 ## Training procedure
 
@@ -76,10 +84,9 @@ The following hyperparameters were used during training:
 | 1.6561        | 2.0   | 360  | 1.7614          | 0.7944   | 0.7575      | 0.7944   | 0.7633   | 0.7944          | 0.7944       | 0.7896       | 0.8458             | 0.7944          | 0.8582          |
 | 0.172         | 3.0   | 540  | 1.8587          | 0.8046   | 0.7749      | 0.8046   | 0.7814   | 0.8046          | 0.8046       | 0.7996       | 0.8567             | 0.8046          | 0.8710          |
 
-
 ### Framework versions
 
 - Transformers 4.28.1
 - Pytorch 2.0.0
 - Datasets 2.11.0
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3