End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9996377394944453
+      value: 0.7166781307466625
     - name: F1
       type: f1
-      value: 0.9997981836528759
+      value: 0.8124204206436981
     - name: Precision
       type: precision
-      value: 0.9997309296381004
+      value: 0.9998169964543063
     - name: Recall
       type: recall
-      value: 0.9998654467168999
+      value: 0.6841833380294918
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ 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 imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0025
-- Accuracy: 0.9996
-- F1: 0.9998
-- Precision: 0.9997
-- Recall: 0.9999
+- Loss: 2.0649
+- Accuracy: 0.7167
+- F1: 0.8124
+- Precision: 0.9998
+- Recall: 0.6842
 
 ## Model description
 

all_results.json

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eval_results.json

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runs/Dec21_04-45-05_Phoenix/events.out.tfevents.1703137745.Phoenix.19392.1

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+oid sha256:1f13edd75dd9cb3a0429be8f62754ea127eed1c10c54e4eabb3c02cacceaf9fe
+size 1032

test_results.json

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+}

train_results.json

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+}

trainer_state.json

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