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
@@ -26,7 +25,7 @@ model-index:
       value: 0.9265375854214123
     - name: Precision
       type: precision
-      value: 0.9269521372101541
+      value: 0.9307429809120586
 ---
 
 <!-- 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
 
-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: 0.1925
+- Loss: 0.1955
 - Accuracy: 0.9265
 - F1 Score: 0.9252
-- Precision: 0.9270
+- Precision: 0.9307
 
 ## Model description
 
@@ -59,30 +58,40 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 64
-- eval_batch_size: 64
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 256
+- total_train_batch_size: 128
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 10
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
-| 1.2212        | 0.96  | 20   | 1.1407          | 0.6429   | 0.6225   | 0.6601    |
-| 0.565         | 1.98  | 41   | 0.5162          | 0.8326   | 0.8311   | 0.8428    |
-| 0.3245        | 2.99  | 62   | 0.3265          | 0.8804   | 0.8784   | 0.8843    |
-| 0.2618        | 4.0   | 83   | 0.2713          | 0.9066   | 0.9054   | 0.9105    |
-| 0.2164        | 4.96  | 103  | 0.2812          | 0.8946   | 0.8929   | 0.8994    |
-| 0.1814        | 5.98  | 124  | 0.2411          | 0.9060   | 0.9043   | 0.9091    |
-| 0.1481        | 6.99  | 145  | 0.2345          | 0.9100   | 0.9084   | 0.9130    |
-| 0.1468        | 8.0   | 166  | 0.2340          | 0.9072   | 0.9055   | 0.9108    |
-| 0.1336        | 8.96  | 186  | 0.1925          | 0.9265   | 0.9252   | 0.9270    |
-| 0.133         | 9.64  | 200  | 0.2021          | 0.9220   | 0.9207   | 0.9235    |
+| 1.1562        | 0.99  | 41   | 1.1378          | 0.6378   | 0.6191   | 0.6537    |
+| 0.4878        | 1.99  | 82   | 0.6477          | 0.7591   | 0.7499   | 0.7874    |
+| 0.2623        | 2.98  | 123  | 0.4410          | 0.8337   | 0.8311   | 0.8488    |
+| 0.1985        | 4.0   | 165  | 0.4660          | 0.8144   | 0.8115   | 0.8455    |
+| 0.1736        | 4.99  | 206  | 0.3230          | 0.8776   | 0.8760   | 0.8894    |
+| 0.124         | 5.99  | 247  | 0.2684          | 0.9026   | 0.9014   | 0.9090    |
+| 0.1278        | 6.98  | 288  | 0.2210          | 0.9180   | 0.9166   | 0.9210    |
+| 0.0959        | 8.0   | 330  | 0.2151          | 0.9208   | 0.9195   | 0.9260    |
+| 0.0849        | 8.99  | 371  | 0.2154          | 0.9220   | 0.9205   | 0.9291    |
+| 0.0805        | 9.99  | 412  | 0.2112          | 0.9191   | 0.9179   | 0.9251    |
+| 0.0682        | 10.98 | 453  | 0.1563          | 0.9385   | 0.9369   | 0.9402    |
+| 0.0624        | 12.0  | 495  | 0.1577          | 0.9396   | 0.9385   | 0.9408    |
+| 0.0415        | 12.99 | 536  | 0.1836          | 0.9305   | 0.9294   | 0.9332    |
+| 0.0465        | 13.99 | 577  | 0.2145          | 0.9203   | 0.9192   | 0.9252    |
+| 0.056         | 14.98 | 618  | 0.1710          | 0.9339   | 0.9325   | 0.9369    |
+| 0.0545        | 16.0  | 660  | 0.2094          | 0.9248   | 0.9236   | 0.9298    |
+| 0.0591        | 16.99 | 701  | 0.1752          | 0.9317   | 0.9303   | 0.9341    |
+| 0.0512        | 17.99 | 742  | 0.1781          | 0.9311   | 0.9297   | 0.9342    |
+| 0.0424        | 18.98 | 783  | 0.1873          | 0.9305   | 0.9293   | 0.9338    |
+| 0.0438        | 19.88 | 820  | 0.1955          | 0.9265   | 0.9252   | 0.9307    |
 
 
 ### Framework versions