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shbA
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food_classifier

Image Classification
Transformers
TensorFlow
vit
generated_from_keras_callback
Inference Endpoints
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End of training

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  1. README.md +10 -10
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,10 +14,10 @@ probably proofread and complete it, then remove this comment. -->
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  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.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.8652
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- - Train Accuracy: 0.75
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- - Validation Loss: 0.7771
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- - Validation Accuracy: 0.75
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  - Epoch: 5
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  ## Model description
@@ -44,12 +44,12 @@ The following hyperparameters were used during training:
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  | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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  |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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- | 0.9228 | 0.7 | 0.9388 | 0.7000 | 0 |
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- | 0.9711 | 0.775 | 0.8639 | 0.7750 | 1 |
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- | 0.8841 | 0.825 | 0.8585 | 0.8250 | 2 |
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- | 0.8757 | 0.65 | 0.8448 | 0.6500 | 3 |
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- | 0.8802 | 0.75 | 0.7883 | 0.75 | 4 |
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- | 0.8652 | 0.75 | 0.7771 | 0.75 | 5 |
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  ### Framework versions
 
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  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.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.6730
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+ - Train Accuracy: 0.675
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+ - Validation Loss: 0.6380
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+ - Validation Accuracy: 0.8000
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  - Epoch: 5
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  ## Model description
 
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  | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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  |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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+ | 0.8438 | 0.625 | 0.6171 | 0.8000 | 0 |
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+ | 0.9123 | 0.625 | 0.8710 | 0.6000 | 1 |
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+ | 0.7847 | 0.7 | 0.5295 | 1.0 | 2 |
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+ | 0.8369 | 0.625 | 0.5829 | 1.0 | 3 |
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+ | 0.7734 | 0.675 | 1.0318 | 0.4000 | 4 |
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+ | 0.6730 | 0.675 | 0.6380 | 0.8000 | 5 |
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  ### Framework versions
tf_model.h5 CHANGED
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