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@@ -24,12 +24,10 @@ model-index:
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  value: 0.8020304568527918
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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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- should probably proofread and complete it, then remove this comment. -->
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- # efficientnet-b5-Brain_Tumors_Image_Classification
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- This model is a fine-tuned version of [google/efficientnet-b5](https://huggingface.co/google/efficientnet-b5) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.9410
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  - Accuracy: 0.8020
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  - Micro precision: 0.8020
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  - Macro precision: 0.8682
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Training procedure
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@@ -76,7 +99,6 @@ The following hyperparameters were used during training:
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  | 1.3872 | 2.0 | 360 | 0.9533 | 0.7843 | 0.7483 | 0.7843 | 0.7548 | 0.7843 | 0.7843 | 0.7819 | 0.8354 | 0.7843 | 0.8471 |
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  | 0.8186 | 3.0 | 540 | 0.9410 | 0.8020 | 0.7736 | 0.8020 | 0.7802 | 0.8020 | 0.8020 | 0.7977 | 0.8535 | 0.8020 | 0.8682 |
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-
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  ### Framework versions
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  - Transformers 4.28.1
 
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  value: 0.8020304568527918
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  ---
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+ <h1>efficientnet-b5-Brain_Tumors_Image_Classification</h1>
 
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+ This model is a fine-tuned version of [google/efficientnet-b5](https://huggingface.co/google/efficientnet-b5).
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  It achieves the following results on the evaluation set:
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  - Loss: 0.9410
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  - Accuracy: 0.8020
 
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  - Micro precision: 0.8020
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  - Macro precision: 0.8682
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+ <div style="text-align: center;">
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+ <h2>
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+ Model Description
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+ </h2>
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+ <a href="https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Image%20Classification/Multiclass%20Classification/Brain%20Tumors%20Image%20Classification%20Comparison/EfficientNet%20-%20Image%20Classification.ipynb">
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+ Click here for the code that I used to create this model.
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+ </a>
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+
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+ This project is part of a comparison of seventeen (17) transformers.
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+ <a href="https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Image%20Classification/Multiclass%20Classification/Brain%20Tumors%20Image%20Classification%20Comparison/README.md">
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+ Click here to see the README markdown file for the full project
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+ </a>
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+ <h2>
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+ Intended Uses & Limitations
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+ </h2>
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+ This model is intended to demonstrate my ability to solve a complex problem using technology.
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+
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+ <h2>
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+ Training & Evaluation Data
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+ </h2>
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+ <a href="https://www.kaggle.com/datasets/sartajbhuvaji/brain-tumor-classification-mri">
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+ Brain Tumor Image Classification Dataset
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+ </a>
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+ <h2>
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+ Sample Images
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+ </h2>
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+ <img src="https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/raw/main/Computer%20Vision/Image%20Classification/Multiclass%20Classification/Brain%20Tumors%20Image%20Classification%20Comparison/Images/Sample%20Images.png" />
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+ <h2>
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+ Class Distribution of Training Dataset
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+ </h2>
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+ <img src="https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/raw/main/Computer%20Vision/Image%20Classification/Multiclass%20Classification/Brain%20Tumors%20Image%20Classification%20Comparison/Images/Class%20Distribution%20-%20Training%20Dataset.png"/>
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+ <h2>
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+ Class Distribution of Evaluation Dataset
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+ </h2>
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+ <img src="https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/raw/main/Computer%20Vision/Image%20Classification/Multiclass%20Classification/Brain%20Tumors%20Image%20Classification%20Comparison/Images/Class%20Distribution%20-%20Testing%20Dataset.png"/>
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+ </div>
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  ## Training procedure
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  | 1.3872 | 2.0 | 360 | 0.9533 | 0.7843 | 0.7483 | 0.7843 | 0.7548 | 0.7843 | 0.7843 | 0.7819 | 0.8354 | 0.7843 | 0.8471 |
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  | 0.8186 | 3.0 | 540 | 0.9410 | 0.8020 | 0.7736 | 0.8020 | 0.7802 | 0.8020 | 0.8020 | 0.7977 | 0.8535 | 0.8020 | 0.8682 |
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  ### Framework versions
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  - Transformers 4.28.1