Update README.md

README.md

@@ -29,7 +29,7 @@ model-index:
 This model returns the artwork style of any image input.
 
 
-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 imagefolder dataset. This is a subset of the artbench-10 dataset (https://www.kaggle.com/datasets/alexanderliao/artbench10), with a train set of 1000 artworks per class and a test set of 100 artworks per class.
+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 imagefolder dataset. This is a subset of the artbench-10 dataset (https://www.kaggle.com/datasets/alexanderliao/artbench10), with a train set of 1000 artworks per class and a validation set of 100 artworks per class.
 It achieves the following results on the evaluation set:
 - Loss: 1.1392
 - Accuracy: 0.5948
@@ -40,11 +40,11 @@ You can find a description of the project that this model was trained for here:
 
 ## Intended uses & limitations
 
-This model only contains 9 out of the 10 artbench-10 classes - it does not contain ukiyo_e.
+This model only contains 9 out of the 10 artbench-10 classes - it does not contain ukiyo_e. This was due to availability and formatting issues.
 
 ## Training and evaluation data
 
-More information needed
+Train: 1000 randomly selected images from artbench-10 (per class). Val: 100 randomly selected images from artbench-10 (per class).
 
 ## Training procedure