Update README.md
Browse files
README.md
CHANGED
@@ -6,6 +6,9 @@ datasets:
|
|
6 |
- imagefolder
|
7 |
metrics:
|
8 |
- accuracy
|
|
|
|
|
|
|
9 |
model-index:
|
10 |
- name: van-base-Brain_Tumors_Image_Classification
|
11 |
results:
|
@@ -22,14 +25,15 @@ model-index:
|
|
22 |
- name: Accuracy
|
23 |
type: accuracy
|
24 |
value: 0.7918781725888325
|
|
|
|
|
|
|
25 |
---
|
26 |
|
27 |
-
|
28 |
-
should probably proofread and complete it, then remove this comment. -->
|
29 |
|
30 |
-
|
31 |
|
32 |
-
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.
|
33 |
It achieves the following results on the evaluation set:
|
34 |
- Loss: 1.7847
|
35 |
- Accuracy: 0.7919
|
@@ -43,17 +47,43 @@ It achieves the following results on the evaluation set:
|
|
43 |
- Micro precision: 0.7919
|
44 |
- Macro precision: 0.8675
|
45 |
|
46 |
-
|
47 |
-
|
48 |
-
|
49 |
-
|
50 |
-
|
51 |
-
|
52 |
-
|
53 |
-
|
54 |
-
|
55 |
-
|
56 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
57 |
|
58 |
## Training procedure
|
59 |
|
@@ -76,10 +106,9 @@ The following hyperparameters were used during training:
|
|
76 |
| 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 |
|
77 |
| 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 |
|
78 |
|
79 |
-
|
80 |
### Framework versions
|
81 |
|
82 |
- Transformers 4.28.1
|
83 |
- Pytorch 2.0.0
|
84 |
- Datasets 2.11.0
|
85 |
-
- Tokenizers 0.13.3
|
|
|
6 |
- imagefolder
|
7 |
metrics:
|
8 |
- accuracy
|
9 |
+
- f1
|
10 |
+
- recall
|
11 |
+
- precision
|
12 |
model-index:
|
13 |
- name: van-base-Brain_Tumors_Image_Classification
|
14 |
results:
|
|
|
25 |
- name: Accuracy
|
26 |
type: accuracy
|
27 |
value: 0.7918781725888325
|
28 |
+
language:
|
29 |
+
- en
|
30 |
+
pipeline_tag: image-classification
|
31 |
---
|
32 |
|
33 |
+
<h1>van-base-Brain_Tumors_Image_Classification</h1>
|
|
|
34 |
|
35 |
+
This model is a fine-tuned version of [Visual-Attention-Network/van-base](https://huggingface.co/Visual-Attention-Network/van-base).
|
36 |
|
|
|
37 |
It achieves the following results on the evaluation set:
|
38 |
- Loss: 1.7847
|
39 |
- Accuracy: 0.7919
|
|
|
47 |
- Micro precision: 0.7919
|
48 |
- Macro precision: 0.8675
|
49 |
|
50 |
+
<div style="text-align: center;">
|
51 |
+
<h2>
|
52 |
+
Model Description
|
53 |
+
</h2>
|
54 |
+
<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”>
|
55 |
+
Click here for the code that I used to create this model.
|
56 |
+
</a>
|
57 |
+
|
58 |
+
This project is part of a comparison of seventeen (17) transformers.
|
59 |
+
|
60 |
+
<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">
|
61 |
+
Click here to see the README markdown file for the full project.
|
62 |
+
</a>
|
63 |
+
<h2>
|
64 |
+
Intended Uses & Limitations
|
65 |
+
</h2>
|
66 |
+
This model is intended to demonstrate my ability to solve a complex problem using technology.
|
67 |
+
|
68 |
+
<h2>
|
69 |
+
Training & Evaluation Data
|
70 |
+
</h2>
|
71 |
+
<a href="https://www.kaggle.com/datasets/sartajbhuvaji/brain-tumor-classification-mri">
|
72 |
+
Brain Tumor Image Classification Dataset
|
73 |
+
</a>
|
74 |
+
<h2>
|
75 |
+
Sample Images
|
76 |
+
</h2>
|
77 |
+
<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" />
|
78 |
+
<h2>
|
79 |
+
Class Distribution of Training Dataset
|
80 |
+
</h2>
|
81 |
+
<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"/>
|
82 |
+
<h2>
|
83 |
+
Class Distribution of Evaluation Dataset
|
84 |
+
</h2>
|
85 |
+
<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"/>
|
86 |
+
</div>
|
87 |
|
88 |
## Training procedure
|
89 |
|
|
|
106 |
| 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 |
|
107 |
| 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 |
|
108 |
|
|
|
109 |
### Framework versions
|
110 |
|
111 |
- Transformers 4.28.1
|
112 |
- Pytorch 2.0.0
|
113 |
- Datasets 2.11.0
|
114 |
+
- Tokenizers 0.13.3
|