commit files to HF hub

README.md

@@ -1,61 +1,31 @@
 ---
-library_name: transformers
 tags:
-- generated_from_trainer
-datasets:
-- imagefolder
+- image-classification
+- pytorch
+- huggingpics
+metrics:
+- accuracy
+
 model-index:
-- name: comixBF
-  results: []
+- name: sanali209/comixBF
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    metrics:
+      - name: Accuracy
+        type: accuracy
+        value: 0.8955321907997131
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# comixBF
-
-This model was trained from scratch on the imagefolder dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.3232
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
+# sanali209/comixBF
 
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 32
-- eval_batch_size: 16
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 4
 
-### Training results
+Autogenerated by HuggingPics🤗🖼️
 
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| No log        | 1.0   | 202  | 0.3801          |
-| No log        | 2.0   | 404  | 0.3245          |
-| 0.4916        | 3.0   | 606  | 0.3441          |
-| 0.4916        | 4.0   | 808  | 0.3232          |
+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).
 
-### Framework versions
 
-- Transformers 4.45.1
-- Pytorch 2.4.1+cu121
-- Datasets 3.0.1
-- Tokenizers 0.20.0
+## Example Images

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "sanali209/comixBF",
+  "_name_or_path": "google/vit-base-patch16-224",
   "architectures": [
     "ViTForImageClassification"
   ],
@@ -7,7 +7,7 @@
   "encoder_stride": 16,
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.0,
-  "hidden_size": 1024,
+  "hidden_size": 768,
   "id2label": {
     "0": "comix bw",
     "1": "comix color",
@@ -17,22 +17,22 @@
   },
   "image_size": 224,
   "initializer_range": 0.02,
-  "intermediate_size": 4096,
+  "intermediate_size": 3072,
   "label2id": {
-    "comix bw": 0,
-    "comix color": 1,
-    "comix cower": 2,
-    "image set": 3,
-    "other": 4
+    "comix bw": "0",
+    "comix color": "1",
+    "comix cower": "2",
+    "image set": "3",
+    "other": "4"
   },
   "layer_norm_eps": 1e-12,
   "model_type": "vit",
-  "num_attention_heads": 16,
+  "num_attention_heads": 12,
   "num_channels": 3,
-  "num_hidden_layers": 24,
+  "num_hidden_layers": 12,
   "patch_size": 16,
   "problem_type": "single_label_classification",
   "qkv_bias": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.45.1"
+  "transformers_version": "4.44.2"
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5f88965fdb9655c79c62192df1e6ffcf20f1c8026c24863e8b5dc57ef882eae5
-size 1213273572
+oid sha256:f8b17bd792ad2330bdd6a3d2fbdbfee5139cd0e4f74da6228846f3ee44fba427
+size 343233204

preprocessor_config.json

@@ -7,7 +7,7 @@
     0.5,
     0.5
   ],
-  "image_processor_type": "ViTImageProcessor",
+  "image_processor_type": "ViTFeatureExtractor",
   "image_std": [
     0.5,
     0.5,

runs/events.out.tfevents.1729171301.6a860356268b.1471.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5958c1f9afe3e34408ad01bafcb3c7a912cda0430ba1df83020c78661f009db9
+size 4936