Model save

README.md

@@ -2,7 +2,6 @@
 license: apache-2.0
 base_model: google/vit-base-patch16-224
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
@@ -16,7 +15,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: custom
+      name: imagefolder
       type: imagefolder
       config: default
       split: train
@@ -24,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.42857142857142855
+      value: 0.3333333333333333
     - name: F1
       type: f1
-      value: 0.3151515151515151
+      value: 0.16666666666666666
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,11 +34,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Model
 
-This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the custom dataset.
+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: 1.3328
-- Accuracy: 0.4286
-- F1: 0.3152
+- Loss: 4.2752
+- Accuracy: 0.3333
+- F1: 0.1667
 
 ## Model description
 
@@ -64,15 +63,18 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 50
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 2.1596        | 50.0  | 50   | 4.2752          | 0.3333   | 0.1667 |
 
 
 ### Framework versions
 
-- Transformers 4.37.2
-- Pytorch 2.1.0+cu121
-- Datasets 2.16.1
-- Tokenizers 0.15.1
+- Transformers 4.39.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2