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Model save

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README.md CHANGED
@@ -2,7 +2,6 @@
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  license: apache-2.0
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  base_model: dima806/deepfake_vs_real_image_detection
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  tags:
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- - image-classification
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  - generated_from_trainer
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  datasets:
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  - imagefolder
@@ -15,7 +14,7 @@ model-index:
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  name: Image Classification
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  type: image-classification
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  dataset:
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- name: ai_real_images
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  type: imagefolder
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  config: default
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  split: train
@@ -23,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8972602739726028
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # realFake-food
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- This model is a fine-tuned version of [dima806/deepfake_vs_real_image_detection](https://huggingface.co/dima806/deepfake_vs_real_image_detection) on the ai_real_images dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2854
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- - Accuracy: 0.8973
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  ## Model description
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@@ -66,8 +65,8 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.3931 | 1.9231 | 100 | 0.3748 | 0.8288 |
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- | 0.1422 | 3.8462 | 200 | 0.2854 | 0.8973 |
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  ### Framework versions
 
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  license: apache-2.0
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  base_model: dima806/deepfake_vs_real_image_detection
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  tags:
 
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  - generated_from_trainer
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  datasets:
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  - imagefolder
 
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  name: Image Classification
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  type: image-classification
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  dataset:
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+ name: imagefolder
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  type: imagefolder
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  config: default
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  split: train
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9041095890410958
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # realFake-food
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+ This model is a fine-tuned version of [dima806/deepfake_vs_real_image_detection](https://huggingface.co/dima806/deepfake_vs_real_image_detection) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2871
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+ - Accuracy: 0.9041
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.3274 | 1.9231 | 100 | 0.2865 | 0.8973 |
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+ | 0.1122 | 3.8462 | 200 | 0.2871 | 0.9041 |
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  ### Framework versions
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