update model card README.md

README.md

@@ -4,9 +4,24 @@ 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: 0.8073852295409182
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,12 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 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:
-- eval_loss: 2.1355
-- eval_accuracy: 0.0220
-- eval_runtime: 173.4607
-- eval_samples_per_second: 5.777
-- eval_steps_per_second: 0.184
-- step: 0
+- Loss: 0.5495
+- Accuracy: 0.8074
 
 ## Model description
 
@@ -51,9 +62,18 @@ 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.782         | 0.99  | 70   | 0.8049          | 0.7275   |
+| 0.5867        | 1.99  | 140  | 0.5791          | 0.7974   |
+| 0.5429        | 2.99  | 210  | 0.5495          | 0.8074   |
+
+
 ### Framework versions
 
-- Transformers 4.21.0
+- Transformers 4.21.1
 - Pytorch 1.12.0+cu113
 - Datasets 2.4.0
 - Tokenizers 0.12.1