Push model using huggingface_hub.

README.md

@@ -1,65 +1,10 @@
 ---
-license: mit
-datasets:
-- sdtemple/colored-shapes
-language:
-- en
-metrics:
-- precision
-- recall
-- roc_auc
-- accuracy
-pipeline_tag: image-classification
 tags:
-- tutorial
+- model_hub_mixin
+- pytorch_model_hub_mixin
 ---
 
-This model predicts the color (among 8 colors) of 1 shape (circle, rectangle, diamond, triangle) in a 224 x 224 x 3 image.
-
-This model is a part of a how to tutorial on fitting PyTorch models.
-
-The model is trained on 2000 examples for each color and shape combo (64,000 samples in total) simulated according to [https://github.com/sdtemple/zootopia3](https://github.com/sdtemple/zootopia3).
-
-The model is tested/evaluated on the dataset [https://huggingface.co/datasets/sdtemple/colored-shapes](https://huggingface.co/datasets/sdtemple/colored-shapes), which has slightly smaller shapes simulated (out of distribution) relative to the training data.  The metrics below can be +- a few points depending on random seed.
-
-- Accuracy: 97%
-- Min precision (red): 91%
-- Max precision (multiple): 100%
-- Min recall (multiple): 95%
-- Max recall (multiple): 100%
-- AUROC (all): >= 99.90%
-
-The model architecture is the following. In light experimentation, I found it important to have multiple convolutions and that too many parameters leads to noisy validation losses by epoch.
-
-```
-MyCNN(
-  (conv_block): Sequential(
-    (0): Conv2d(3, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
-    (1): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
-    (2): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
-    (3): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
-    (4): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
-    (5): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
-    (6): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
-    (7): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
-    (8): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
-    (9): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
-    (10): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
-    (11): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
-    (12): Conv2d(16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
-    (13): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
-    (14): AvgPool2d(kernel_size=2, stride=2, padding=0)
-  )
-  (linear_block): Sequential(
-    (0): Linear(in_features=784, out_features=16, bias=True)
-    (1): BatchNorm1d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
-    (2): ReLU()
-    (3): Dropout(p=0.2, inplace=False)
-    (4): Linear(in_features=16, out_features=16, bias=True)
-    (5): BatchNorm1d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
-    (6): ReLU()
-    (7): Dropout(p=0.2, inplace=False)
-  )
-  (output_block): Linear(in_features=16, out_features=4, bias=True)
-)
-```
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Code: [More Information Needed]
+- Paper: [More Information Needed]
+- Docs: [More Information Needed]

config.json

@@ -1,16 +1,15 @@
 {
-  "model_type": "custom_pytorch_model",
-  "num_classes": 8,
+  "dropout": 0.2,
   "height": 224,
-  "width": 224,
-  "num_input_channels": 3,
+  "hidden_dim": 16,
+  "kernel_size": 3,
+  "num_classes": 8,
   "num_cnn_channels": 16,
   "num_cnn_layers": 3,
-  "hidden_dim": 16,
+  "num_input_channels": 3,
   "num_layers": 1,
-  "kernel_size": 3,
-  "stride": 1,
   "padding": 1,
   "pooling": 2,
-  "dropout": 0.2
+  "stride": 1,
+  "width": 224
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f9a99ee56f6aaf4b1ed344bde5365646d1d5e39315d595d4524db26c796a01a1
+oid sha256:52c834d91ee5344a918d6a7ab0b71768f76aa88d64052774631e8296ed58c30a
 size 96856