Model save

README.md

@@ -1,17 +1,27 @@
 ---
-license: apache-2.0
 base_model: d071696/vit-finetune-scrap
 tags:
-- image-to-text
-- image-classification
 - generated_from_trainer
 datasets:
-- imagefolder
+- arrow
 metrics:
 - accuracy
 model-index:
 - name: vit-finetune-scrap
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: arrow
+      type: arrow
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9694238815577728
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -19,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # vit-finetune-scrap
 
-This model is a fine-tuned version of [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the d071696/scraps1 dataset.
+This model is a fine-tuned version of [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the arrow dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9895
-- Accuracy: 1.0
+- Loss: 0.1116
+- Accuracy: 0.9694
 
 ## Model description
 
@@ -51,6 +61,9 @@ The following hyperparameters were used during training:
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1326        | 2.57  | 1000 | 0.1116          | 0.9694   |
 
 
 ### Framework versions

runs/Mar29_16-45-17_X5C922065N/events.out.tfevents.1711727303.X5C922065N.53009.3

@@ -1,3 +1,3 @@
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+size 38457