commit files to HF hub

README.md

@@ -1,56 +1,56 @@
 ---
-tags:
-- image-classification
-- pytorch
-- huggingpics
-metrics:
-- accuracy
-
-model-index:
-- name: krenzcolor_chkpt_classifier
-  results:
-  - task:
-      name: Image Classification
-      type: image-classification
+    tags:
+    - image-classification
+    - pytorch
+    - huggingpics
     metrics:
-      - name: Accuracy
-        type: accuracy
-        value: 0.5892857313156128
----
-
-# krenzcolor_chkpt_classifier
-
-
-Autogenerated by HuggingPics🤗🖼️
-
-Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
-
-Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
-
-
-## Example Images
+    - accuracy
 
+    model-index:
+    - name: krenzcolor_chkpt_classifier
+    results:
+    - task:
+        name: Image Classification
+        type: image-classification
+        metrics:
+        - name: Accuracy
+            type: accuracy
+            value: 0.4107142984867096
+    ---
 
-#### chk1_fail
+    # krenzcolor_chkpt_classifier
 
-![chk1_fail](images/chk1_fail.jpg)
+    
+    Autogenerated by HuggingPics🤗🖼️
 
-#### chk1_pass
+    Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
 
-![chk1_pass](images/chk1_pass.jpg)
+    Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
+    
 
-#### chk2_fail
+    ## Example Images
 
-![chk2_fail](images/chk2_fail.jpg)
+    
+    #### chk1_fail
 
-#### chk2_pass
+    ![chk1_fail](images/chk1_fail.jpg)
+    
+    #### chk1_pass
 
-![chk2_pass](images/chk2_pass.jpg)
+    ![chk1_pass](images/chk1_pass.jpg)
+    
+    #### chk2_fail
 
-#### chk3_fail
+    ![chk2_fail](images/chk2_fail.jpg)
+    
+    #### chk2_pass
 
-![chk3_fail](images/chk3_fail.jpg)
+    ![chk2_pass](images/chk2_pass.jpg)
+    
+    #### chk3_fail
 
-#### chk3_pass
+    ![chk3_fail](images/chk3_fail.jpg)
+    
+    #### chk3_pass
 
-![chk3_pass](images/chk3_pass.jpg)
+    ![chk3_pass](images/chk3_pass.jpg)

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "google/vit-base-patch16-384",
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
   "architectures": [
     "ViTForImageClassification"
   ],
@@ -16,21 +16,21 @@
     "4": "chk3_fail",
     "5": "chk3_pass"
   },
-  "image_size": 384,
+  "image_size": 224,
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "chk1_fail": "0",
-    "chk1_pass": "1",
-    "chk2_fail": "2",
-    "chk2_pass": "3",
-    "chk3_fail": "4",
-    "chk3_pass": "5"
+    "chk1_fail": 0,
+    "chk1_pass": 1,
+    "chk2_fail": 2,
+    "chk2_pass": 3,
+    "chk3_fail": 4,
+    "chk3_pass": 5
   },
   "layer_norm_eps": 1e-12,
   "model_type": "vit",
   "num_attention_heads": 12,
-  "num_channels": 3,
+  "num_channels": 6,
   "num_hidden_layers": 12,
   "patch_size": 16,
   "problem_type": "single_label_classification",

preprocessor_config.json

@@ -13,5 +13,5 @@
     0.5
   ],
   "resample": 2,
-  "size": 384
+  "size": 224
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
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runs/events.out.tfevents.1666941512.sa103.15721.0

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