update model card README.md

README.md

@@ -1,24 +1,23 @@
 ---
 license: apache-2.0
 tags:
-- image-classification
 - generated_from_trainer
 metrics:
 - accuracy
 model-index:
-- name: vit-base-beans-demo-v5
+- name: vit-diabetic-retinopathy-classification
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# vit-base-beans-demo-v5
+# vit-diabetic-retinopathy-classification
 
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the diabetic-retinopathy-classification dataset.
+This model is a fine-tuned version of [Kontawat/vit-diabetic-retinopathy-classification](https://huggingface.co/Kontawat/vit-diabetic-retinopathy-classification) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7260
-- Accuracy: 0.7263
+- Loss: 1.0460
+- Accuracy: 0.7287
 
 ## Model description
 
@@ -38,26 +37,24 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0002
-- train_batch_size: 16
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 4
+- num_epochs: 6
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.9235        | 0.47  | 100  | 0.8972          | 0.6493   |
-| 0.9253        | 0.95  | 200  | 0.9151          | 0.6635   |
-| 0.8371        | 1.42  | 300  | 0.8071          | 0.6931   |
-| 0.7355        | 1.9   | 400  | 0.7563          | 0.7073   |
-| 0.6532        | 2.37  | 500  | 0.7543          | 0.6896   |
-| 0.5982        | 2.84  | 600  | 0.7260          | 0.7263   |
-| 0.4276        | 3.32  | 700  | 0.7346          | 0.7239   |
-| 0.4935        | 3.79  | 800  | 0.7490          | 0.7133   |
+| 0.5645        | 0.94  | 100  | 0.7731          | 0.7239   |
+| 0.3971        | 1.89  | 200  | 0.8123          | 0.7038   |
+| 0.3239        | 2.83  | 300  | 0.8204          | 0.7239   |
+| 0.2178        | 3.77  | 400  | 0.9085          | 0.7204   |
+| 0.18          | 4.72  | 500  | 1.0284          | 0.7310   |
+| 0.0501        | 5.66  | 600  | 1.0460          | 0.7287   |
 
 
 ### Framework versions