End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9772727272727273
+      value: 0.9715909090909091
 ---
 
 <!-- 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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1798
-- Accuracy: 0.9773
+- Loss: 0.0966
+- Accuracy: 0.9716
 
 ## Model description
 
@@ -61,15 +61,17 @@ 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: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.7289        | 0.98  | 23   | 0.4584          | 0.9432   |
-| 0.2906        | 2.0   | 47   | 0.2243          | 0.9432   |
-| 0.1977        | 2.94  | 69   | 0.1798          | 0.9773   |
+| 0.1378        | 0.98  | 23   | 0.1374          | 0.9716   |
+| 0.0887        | 2.0   | 47   | 0.0863          | 0.9886   |
+| 0.0662        | 2.98  | 70   | 0.0724          | 0.9830   |
+| 0.0677        | 4.0   | 94   | 0.0975          | 0.9659   |
+| 0.0691        | 4.89  | 115  | 0.0966          | 0.9716   |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:8033b2890e69e01aaa481b3517b3ea503720423a62f074808c9f00e1e15a12c7
 size 343227052