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metadata
license: apache-2.0
base_model: hustvl/yolos-tiny
tags:
  - generated_from_trainer
  - medical
  - science
model-index:
  - name: yolos-tiny-Brain_Tumor_Detection
    results: []
datasets:
  - Francesco/brain-tumor-m2pbp
language:
  - en
pipeline_tag: object-detection

yolos-tiny-Brain_Tumor_Detection

This model is a fine-tuned version of hustvl/yolos-tiny.

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

**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.

Training and evaluation data

Dataset Source: https://huggingface.co/datasets/Francesco/brain-tumor-m2pbp

Example

Example Image

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