Update model card with more detailed info after pushing to hub

README.md

@@ -5,14 +5,16 @@ tags:
 model-index:
 - name: food-classifier
   results: []
+datasets:
+- food101
+metrics:
+- accuracy
+library_name: transformers
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
-
 # food-classifier
 
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the food101 dataset.
 It achieves the following results on the evaluation set:
 - Train Loss: 0.2136
 - Validation Loss: 0.2284
@@ -21,17 +23,15 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This is an image classification model fine tuned from the Google Vision Transformer (ViT) to classify images of food. 
 
 ## Intended uses & limitations
 
-More information needed
+For messing around!
 
 ## Training and evaluation data
 
-More information needed
-
-## Training procedure
+The training set contained 101 food classes, over a dataset of 101,000 images. The train/eval split was 80/20
 
 ### Training hyperparameters
 
@@ -55,4 +55,4 @@ The following hyperparameters were used during training:
 - Transformers 4.30.2
 - TensorFlow 2.12.0
 - Datasets 2.13.1
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3