đ yolos-tiny-Brain_Tumor_Detection
This model is a fine - tuned version of hustvl/yolos-tiny, designed for brain tumor detection.
đ Quick Start
This model is a fine - tuned version of hustvl/yolos-tiny.
⨠Features
Model description
For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Object%20Detection/Brain%20Tumors/Brain_Tumor_m2pbp_Object_Detection_YOLOS.ipynb
â ī¸ Important Note
If you intend on trying this project yourself, I highly recommend using (at least) the yolos - small checkpoint.
Intended uses & limitations
This model is intended to demonstrate my ability to solve a complex problem using technology.
đĻ Installation
No installation steps are provided in the original document.
đģ Usage Examples
No code examples are provided in the original document.
đ Documentation
Training and evaluation data
Dataset Source: https://huggingface.co/datasets/Francesco/brain-tumor-m2pbp
Example
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e - 05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Metric Name |
IoU |
Area |
maxDets |
Metric Value |
| Average Precision (AP) |
IoU = 0.50:0.95 |
area = all |
maxDets = 100 |
0.185 |
| Average Precision (AP) |
IoU = 0.50 |
area = all |
maxDets = 100 |
0.448 |
| Average Precision (AP) |
IoU = 0.75 |
area = all |
maxDets = 100 |
0.126 |
| Average Precision (AP) |
IoU = 0.50:0.95 |
area = small |
maxDets = 100 |
0.001 |
| Average Precision (AP) |
IoU = 0.50:0.95 |
area = medium |
maxDets = 100 |
0.080 |
| Average Precision (AP) |
IoU = 0.50:0.95 |
area = large |
maxDets = 100 |
0.296 |
| Average Recall (AR) |
IoU = 0.50:0.95 |
area = all |
maxDets = 1 |
0.254 |
| Average Recall (AR) |
IoU = 0.50:0.95 |
area = all |
maxDets = 10 |
0.353 |
| Average Recall (AR) |
IoU = 0.50:0.95 |
area = all |
maxDets = 100 |
0.407 |
| Average Recall (AR) |
IoU = 0.50:0.95 |
area = small |
maxDets = 100 |
0.036 |
| Average Recall (AR) |
IoU = 0.50:0.95 |
area = medium |
maxDets = 100 |
0.312 |
| Average Recall (AR) |
IoU = 0.50:0.95 |
area = large |
maxDets = 100 |
0.565 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3
đ License
This model is licensed under the Apache 2.0 license.
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