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@@ -6,6 +6,9 @@ datasets:
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  - imagefolder
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  metrics:
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  - accuracy
 
 
 
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  model-index:
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  - name: van-base-Brain_Tumors_Image_Classification
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  results:
@@ -22,14 +25,15 @@ model-index:
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  - name: Accuracy
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  type: accuracy
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  value: 0.7918781725888325
 
 
 
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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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- # van-base-Brain_Tumors_Image_Classification
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- This model is a fine-tuned version of [Visual-Attention-Network/van-base](https://huggingface.co/Visual-Attention-Network/van-base) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 1.7847
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  - Accuracy: 0.7919
@@ -43,17 +47,43 @@ It achieves the following results on the evaluation set:
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  - Micro precision: 0.7919
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  - Macro precision: 0.8675
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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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@@ -76,10 +106,9 @@ The following hyperparameters were used during training:
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  | 1.3357 | 2.0 | 360 | 1.9359 | 0.7792 | 0.7314 | 0.7792 | 0.7411 | 0.7792 | 0.7792 | 0.7764 | 0.8467 | 0.7792 | 0.8636 |
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  | 0.1229 | 3.0 | 540 | 1.7847 | 0.7919 | 0.7588 | 0.7919 | 0.7665 | 0.7919 | 0.7919 | 0.7865 | 0.8505 | 0.7919 | 0.8675 |
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-
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  ### Framework versions
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  - Transformers 4.28.1
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  - Pytorch 2.0.0
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  - Datasets 2.11.0
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- - Tokenizers 0.13.3
 
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  - imagefolder
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  metrics:
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  - accuracy
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+ - f1
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+ - recall
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+ - precision
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  model-index:
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  - name: van-base-Brain_Tumors_Image_Classification
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  results:
 
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  - name: Accuracy
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  type: accuracy
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  value: 0.7918781725888325
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+ language:
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+ - en
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+ pipeline_tag: image-classification
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  ---
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+ <h1>van-base-Brain_Tumors_Image_Classification</h1>
 
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+ This model is a fine-tuned version of [Visual-Attention-Network/van-base](https://huggingface.co/Visual-Attention-Network/van-base).
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  It achieves the following results on the evaluation set:
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  - Loss: 1.7847
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  - Accuracy: 0.7919
 
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  - Micro precision: 0.7919
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  - Macro precision: 0.8675
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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/VAN%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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+
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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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  | 1.3357 | 2.0 | 360 | 1.9359 | 0.7792 | 0.7314 | 0.7792 | 0.7411 | 0.7792 | 0.7792 | 0.7764 | 0.8467 | 0.7792 | 0.8636 |
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  | 0.1229 | 3.0 | 540 | 1.7847 | 0.7919 | 0.7588 | 0.7919 | 0.7665 | 0.7919 | 0.7919 | 0.7865 | 0.8505 | 0.7919 | 0.8675 |
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  ### Framework versions
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  - Transformers 4.28.1
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  - Pytorch 2.0.0
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  - Datasets 2.11.0
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+ - Tokenizers 0.13.3