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README.md

@@ -24,10 +24,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8580527752502275
+      value: 0.8589626933575978
     - name: F1
       type: f1
-      value: 0.8173302107728336
+      value: 0.8116646415552855
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -37,12 +37,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 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 stool-image dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3669
-- Auroc: 0.9121
-- Accuracy: 0.8581
-- Sensitivity: 0.7756
-- Specificty: 0.9153
-- F1: 0.8173
+- Loss: 0.3651
+- Auroc: 0.9090
+- Accuracy: 0.8590
+- Sensitivity: 0.7422
+- Specificty: 0.9399
+- F1: 0.8117
 
 ## Model description
 
@@ -67,14 +67,15 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 2
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Auroc  | Accuracy | Sensitivity | Specificty | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-----------:|:----------:|:------:|
-| 0.4071        | 0.98  | 100  | 0.4415          | 0.8876 | 0.8179   | 0.6629      | 0.9552     | 0.7738 |
+| 0.3775        | 0.98  | 100  | 0.4743          | 0.9005 | 0.7863   | 0.5899      | 0.9602     | 0.7216 |
+| 0.3238        | 1.96  | 200  | 0.4048          | 0.8973 | 0.8232   | 0.7360      | 0.9005     | 0.7964 |
 
 
 ### Framework versions

all_results.json

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 }

config.json

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-    "0": "0",
-    "1": "1"
+    "0": "Normal",
+    "1": "Abnormal"
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   "label2id": {
-    "0": "0",
-    "1": "1"
+    "Abnormal": "1",
+    "Normal": "0"
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   "model_type": "vit",

eval_results.json

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