Training Completed!_2

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9058823529411765
+      value: 0.9176470588235294
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4062
-- Accuracy: 0.9059
+- Loss: 0.3352
+- Accuracy: 0.9176
 
 ## Model description
 

all_results.json

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 }

config.json

@@ -9,17 +9,17 @@
   "hidden_dropout_prob": 0.0,
   "hidden_size": 768,
   "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2"
+    "0": "normal",
+    "1": "Cancer",
+    "2": "Benign"
   },
   "image_size": 224,
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_2": 2
+    "Benign": 2,
+    "Cancer": 1,
+    "normal": 0
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   "layer_norm_eps": 1e-12,
   "model_type": "vit",

eval_results.json

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+    "eval_steps_per_second": 4.936
 }

model.safetensors

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runs/May10_16-16-07_697233a92faa/events.out.tfevents.1715357768.697233a92faa.581.4

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train_results.json

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 }

trainer_state.json

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training_args.bin

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