Model save

README.md

@@ -1,4 +1,6 @@
 ---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
 tags:
 - generated_from_trainer
 datasets:
@@ -20,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6818181818181818
+      value: 0.5909090909090909
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -28,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # swin-tiny-patch4-window7-224-finetuned-eurosat-kornia
 
-This model was trained from scratch on the imagefolder 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: 0.6445
-- Accuracy: 0.6818
+- Loss: 0.5886
+- Accuracy: 0.5909
 
 ## Model description
 
@@ -65,11 +67,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 3    | 1.6664          | 0.5455   |
-| No log        | 2.0   | 6    | 0.7899          | 0.7273   |
-| No log        | 3.0   | 9    | 0.7704          | 0.7273   |
-| 0.3108        | 4.0   | 12   | 0.6269          | 0.7273   |
-| 0.3108        | 5.0   | 15   | 0.6445          | 0.6818   |
+| No log        | 1.0   | 3    | 0.6243          | 0.6818   |
+| No log        | 2.0   | 6    | 0.5460          | 0.7273   |
+| No log        | 3.0   | 9    | 0.5540          | 0.7273   |
+| 0.6502        | 4.0   | 12   | 0.5747          | 0.6818   |
+| 0.6502        | 5.0   | 15   | 0.5886          | 0.5909   |
 
 
 ### Framework versions

model.safetensors

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 size 343223968

runs/Jan11_08-11-35_884473a9f125/events.out.tfevents.1704960712.884473a9f125.5987.14

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