gradio article added as well

app.py

@@ -22,7 +22,7 @@ with open('gradio_article.md') as f:
 
 interface_options = {
     "title": "Food Image Classifier (Food-101|ResNet50|fast.ai)",
-    "description": "A food image classifier trained on the Food-101 dataset, using ResNet50 and fast.ai.(https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/)",
+    "description": "A food image classifier trained on the Food-101 dataset, using ResNet50 via fast.ai.(Dataset from : https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/)",
     "article": article,
     "examples" : [f'{EXAMPLES_PATH}/{f.name}' for f in EXAMPLES_PATH.iterdir()],
     "interpretation": "default",

gradio_article.md

@@ -1,7 +1,22 @@
-# H1
+## Dataset
 
-Some text here
+The Food-101 dataset, originally made available at https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/ is a data set of 101 food categories, with 101'000 images.
 
-## H2
 
-Some more text here
+## Training
+
+Fast.ai was used to train this classifier with a ResNet50 vision learner, without much customization.
+
+The final fine tuning of the training loop resulted in the following losses.
+
+| epoch	| train_loss	| valid_loss	| error_rate	| time  |
+|-------|---------------|---------------|---------------|-------|
+| 0	| 1.358123	| 1.100139	| 0.288713	| 05:14 |
+| 1	| 1.129988	| 0.985213	| 0.260693	| 05:12 |
+| 2	| 0.964907	| 0.909715	| 0.241337	| 05:17 |
+| 3	| 0.804738	| 0.843515	| 0.222475	| 05:19 |
+| 4	| 0.638846	| 0.795957	| 0.205347	| 05:16 |
+| 5	| 0.475434	| 0.750069	| 0.192673	| 05:15 |
+| 6	| 0.345060	| 0.742432	| 0.185198	| 05:12 |
+| 7	| 0.247938	| 0.728758	| 0.177624	| 05:12 |
+| 8	| 0.214708	| 0.727486	| 0.177871	| 05:11 |