Model save

README.md

@@ -5,9 +5,28 @@ tags:
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
+- f1
 model-index:
 - name: custom
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8922438630863202
+    - name: F1
+      type: f1
+      value: 0.7977454472509276
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +35,10 @@ should probably proofread and complete it, then remove this comment. -->
 # custom
 
 This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3082
+- Accuracy: 0.8922
+- F1: 0.7977
 
 ## Model description
 

all_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 1.0,
+    "eval_accuracy": 0.8922438630863202,
+    "eval_f1": 0.7977454472509276,
+    "eval_loss": 1.308197021484375,
+    "eval_runtime": 252.0312,
+    "eval_samples_per_second": 34.428,
+    "eval_steps_per_second": 4.305
+}

eval_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 1.0,
+    "eval_accuracy": 0.8922438630863202,
+    "eval_f1": 0.7977454472509276,
+    "eval_loss": 1.308197021484375,
+    "eval_runtime": 252.0312,
+    "eval_samples_per_second": 34.428,
+    "eval_steps_per_second": 4.305
+}

runs/Nov08_07-23-50_e2600d548b5f/events.out.tfevents.1699432001.e2600d548b5f.6303.1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af4caf5440480904b5b837c4d5db4d21db544df3a998c3c21aebdf2c4f658311
+size 457