Model save

README.md

@@ -17,12 +17,12 @@ model-index:
       name: imagefolder
       type: imagefolder
       config: default
-      split: train
+      split: test
       args: default
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8683473389355743
+      value: 0.8634920634920635
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4009
-- Accuracy: 0.8683
+- Loss: 0.4464
+- Accuracy: 0.8635
 
 ## Model description
 
@@ -61,15 +61,13 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 1
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.9308        | 0.9801 | 37   | 0.5692          | 0.8301   |
-| 0.7052        | 1.9868 | 75   | 0.4806          | 0.8469   |
-| 0.5414        | 2.9404 | 111  | 0.4009          | 0.8683   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.8084        | 1.0   | 42   | 0.4464          | 0.8635   |
 
 
 ### Framework versions