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: reitBF
-  results: []
+- name: sanali209/reitBF
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    metrics:
+      - name: Accuracy
+        type: accuracy
+        value: 0.7050885558128357
 ---
 
-<!-- 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. -->
-
-# reitBF
-
-This model was trained from scratch on the imagefolder dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4243
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
+# sanali209/reitBF
 
-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 |
-|:-------------:|:-----:|:----:|:---------------:|
-| 0.6049        | 1.0   | 544  | 0.4642          |
-| 0.5146        | 2.0   | 1088 | 0.4316          |
-| 0.4582        | 3.0   | 1632 | 0.4249          |
-| 0.4342        | 4.0   | 2176 | 0.4243          |
+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 4.44.2
-- Pytorch 2.4.0+cu121
-- Datasets 3.0.0
-- Tokenizers 0.19.1
+## Example Images

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "sanali209/reitBF",
+  "_name_or_path": "google/vit-base-patch16-224",
   "architectures": [
     "ViTForImageClassification"
   ],
@@ -17,9 +17,9 @@
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "high": 0,
-    "low": 1,
-    "normal": 2
+    "high": "0",
+    "low": "1",
+    "normal": "2"
   },
   "layer_norm_eps": 1e-12,
   "model_type": "vit",

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ec1be3f73793601ce6b59a0bf3bfd3d209a0d4423897af01e6278db132b40fab
+oid sha256:aab4e93624b5613497fe4381bf583baae9727fda14d05979b1844ab63cfd90a7
 size 343227052

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.1730530863.14fc26b0d183.1463.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9494215c8968b4c89b4d508cd405043fb94a52b1ec21868e7d7aa25e44fe7b2d
+size 10237