update model card README.md

README.md

@@ -1,7 +1,6 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
 - generated_from_trainer
 datasets:
 - imagefolder
@@ -15,7 +14,7 @@ model-index:
       name: Image Classification
       type: image-classification
     dataset:
-      name: Brain Tumor
+      name: imagefolder
       type: imagefolder
       config: default
       split: train
@@ -23,10 +22,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9698177676537585
+      value: 0.9584282460136674
     - name: Precision
       type: precision
-      value: 0.9677462875813125
+      value: 0.9575941658443274
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,12 +33,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_05
 
-This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the Brain Tumor dataset.
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0792
-- Accuracy: 0.9698
-- F1 Score: 0.9686
-- Precision: 0.9677
+- Loss: 0.1136
+- Accuracy: 0.9584
+- F1 Score: 0.9562
+- Precision: 0.9576
 
 ## Model description
 
@@ -73,16 +72,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
-| 1.3233        | 0.98  | 13   | 0.7676          | 0.7813   | 0.7713   | 0.7796    |
-| 0.6659        | 1.96  | 26   | 0.2467          | 0.9146   | 0.9111   | 0.9128    |
-| 0.3122        | 2.94  | 39   | 0.1592          | 0.9442   | 0.9417   | 0.9410    |
-| 0.1505        | 4.0   | 53   | 0.1241          | 0.9607   | 0.9586   | 0.9600    |
-| 0.1369        | 4.98  | 66   | 0.1187          | 0.9584   | 0.9568   | 0.9562    |
-| 0.1014        | 5.96  | 79   | 0.1032          | 0.9630   | 0.9614   | 0.9605    |
-| 0.0701        | 6.94  | 92   | 0.0938          | 0.9641   | 0.9626   | 0.9616    |
-| 0.0573        | 8.0   | 106  | 0.0941          | 0.9647   | 0.9631   | 0.9623    |
-| 0.0614        | 8.98  | 119  | 0.0830          | 0.9687   | 0.9674   | 0.9666    |
-| 0.0534        | 9.81  | 130  | 0.0792          | 0.9698   | 0.9686   | 0.9677    |
+| 1.2801        | 0.98  | 13   | 0.6953          | 0.7335   | 0.6819   | 0.7815    |
+| 0.5928        | 1.96  | 26   | 0.3691          | 0.8440   | 0.8218   | 0.8629    |
+| 0.3122        | 2.94  | 39   | 0.1664          | 0.9402   | 0.9377   | 0.9373    |
+| 0.1513        | 4.0   | 53   | 0.1292          | 0.9493   | 0.9468   | 0.9467    |
+| 0.1227        | 4.98  | 66   | 0.1030          | 0.9601   | 0.9577   | 0.9585    |
+| 0.1201        | 5.96  | 79   | 0.1312          | 0.9522   | 0.9496   | 0.9508    |
+| 0.0806        | 6.94  | 92   | 0.1306          | 0.9522   | 0.9494   | 0.9520    |
+| 0.0645        | 8.0   | 106  | 0.1474          | 0.9482   | 0.9457   | 0.9490    |
+| 0.0668        | 8.98  | 119  | 0.0947          | 0.9613   | 0.9589   | 0.9600    |
+| 0.0577        | 9.81  | 130  | 0.1136          | 0.9584   | 0.9562   | 0.9576    |
 
 
 ### Framework versions