BhavanaMalla
/

image_classification_food101VITmodel

Image Classification

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BhavanaMalla commited on Dec 30, 2023

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@@ -17,8 +17,8 @@ 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 an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.5156
-- Accuracy: 0.715
 ## Model description
@@ -52,9 +52,9 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 4.2745        | 0.96  | 12   | 3.4188          | 0.74     |
-| 3.1492        | 2.0   | 25   | 2.6873          | 0.7      |
-| 2.6294        | 2.88  | 36   | 2.5156          | 0.715    |
 ### Framework versions

 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 2.5424
+- Accuracy: 0.7
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 4.2504        | 0.96  | 12   | 3.4853          | 0.695    |
+| 3.1914        | 2.0   | 25   | 2.7080          | 0.695    |
+| 2.6501        | 2.88  | 36   | 2.5424          | 0.7      |
 ### Framework versions