update model card README.md

README.md

@@ -1,7 +1,5 @@
 ---
 tags:
-- image-classification
-- vision
 - generated_from_trainer
 datasets:
 - beans
@@ -20,7 +18,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9699248120300752
+      value: 0.9022556390977443
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,8 +28,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the beans dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1014
-- Accuracy: 0.9699
+- Loss: 0.2188
+- Accuracy: 0.9023
 
 ## Model description
 
@@ -57,17 +55,13 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 5.0
+- num_epochs: 1.0
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.9524        | 1.0   | 130  | 0.2826          | 0.8647   |
-| 0.3596        | 2.0   | 260  | 0.2216          | 0.9023   |
-| 0.2419        | 3.0   | 390  | 0.1324          | 0.9474   |
-| 0.3248        | 4.0   | 520  | 0.1124          | 0.9699   |
-| 0.1557        | 5.0   | 650  | 0.1014          | 0.9699   |
+| 0.5679        | 1.0   | 130  | 0.2188          | 0.9023   |
 
 
 ### Framework versions