Model save

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - imagefolder
+metrics:
+- accuracy
 model-index:
 - name: swin-tiny-patch4-window7-224-finetuned-eurosat
-  results: []
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8155574762316335
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
 # swin-tiny-patch4-window7-224-finetuned-eurosat
 
 This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9371
+- Accuracy: 0.8156
 
 ## Model description
 
@@ -45,6 +63,15 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 3
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9174        | 1.0   | 406  | 1.3901          | 0.7210   |
+| 1.5653        | 2.0   | 813  | 1.0358          | 0.7938   |
+| 1.4324        | 2.99  | 1218 | 0.9371          | 0.8156   |
+
+
 ### Framework versions
 
 - Transformers 4.36.1