SeyedAli/Food-Image-Classification-VIT

README.md

@@ -1,29 +1,29 @@
 ---
-license: mit
+license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
 datasets:
 - food101
 model-index:
-- name: Food-Image-Classification-VIT
+- name: vit-base-food-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. -->
 
-# Food-Image-Classification-VIT
+# vit-base-food-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 food101 dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 1.1551
-- eval_accuracy: 0.7081
-- eval_runtime: 407.104
-- eval_samples_per_second: 62.023
-- eval_steps_per_second: 7.755
-- epoch: 0.23
-- step: 1098
+- eval_loss: 1.0611
+- eval_accuracy: 0.7274
+- eval_runtime: 411.0682
+- eval_samples_per_second: 61.425
+- eval_steps_per_second: 7.68
+- epoch: 0.15
+- step: 718
 
 ## Model description
 

all_results.json

@@ -1,4 +1,4 @@
 {
-    "eval_accuracy": 0.708079207920792,
-    "eval_loss": 1.1550568342208862
+    "eval_accuracy": 0.7274455445544554,
+    "eval_loss": 1.0611485242843628
 }

eval_results.json

@@ -1,4 +1,4 @@
 {
-    "eval_accuracy": 0.708079207920792,
-    "eval_loss": 1.1550568342208862
+    "eval_accuracy": 0.7274455445544554,
+    "eval_loss": 1.0611485242843628
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
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 size 343573229