update model card README.md

README.md

@@ -4,36 +4,9 @@ tags:
 - generated_from_trainer
 datasets:
 - imagefolder
-metrics:
-- accuracy
-- f1
-- recall
-- precision
 model-index:
 - name: swin-tiny-patch4-window7-224-finetuned-brainTumorData
-  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: 0.9977843426883308
-    - name: F1
-      type: f1
-      value: 0.9984067976633033
-    - name: Recall
-      type: recall
-      value: 0.9978768577494692
-    - name: Precision
-      type: precision
-      value: 0.9989373007438895
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +16,15 @@ 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:
-- Loss: 0.0101
-- Accuracy: 0.9978
-- F1: 0.9984
-- Recall: 0.9979
-- Precision: 0.9989
+- eval_loss: 0.7449
+- eval_accuracy: 0.4357
+- eval_f1: 0.4203
+- eval_recall: 0.2882
+- eval_precision: 0.7759
+- eval_runtime: 69.1743
+- eval_samples_per_second: 19.574
+- eval_steps_per_second: 0.622
+- step: 0
 
 ## Model description
 
@@ -77,16 +54,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 4
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
-| 0.1884        | 1.0   | 95   | 0.0706          | 0.9705   | 0.9787 | 0.9756 | 0.9818    |
-| 0.1134        | 2.0   | 190  | 0.0364          | 0.9889   | 0.9920 | 0.9883 | 0.9957    |
-| 0.1031        | 3.0   | 285  | 0.0116          | 0.9963   | 0.9973 | 0.9947 | 1.0       |
-| 0.0746        | 4.0   | 380  | 0.0101          | 0.9978   | 0.9984 | 0.9979 | 0.9989    |
-
-
 ### Framework versions
 
 - Transformers 4.23.1