--- license: apache-2.0 base_model: hustvl/yolos-small tags: - generated_from_trainer - medical - biology model-index: - name: yolos-small-Abdomen_MRI results: [] datasets: - Francesco/abdomen-mri language: - en metrics: - mean_iou pipeline_tag: object-detection --- # yolos-small-Abdomen_MRI This model is a fine-tuned version of [hustvl/yolos-small](https://huggingface.co/hustvl/yolos-small). ## Model description https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Object%20Detection/Abdomen%20MRIs%20Object%20Detection/Abdomen_MRI_Object_Detection_YOLOS.ipynb ## 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/abdomen-mri ## 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: 15 ### Training results | Metric Name | IoU | Area | maxDets | Value | |:-----:|:-----:|:-----:|:-----:|:-----:| | Average Precision (AP) | 0.50:0.95 | all | 100 | 0.453 | | Average Precision (AP) | 0.50 | all | 100 | 0.928 | | Average Precision (AP) | 0.75 | all | 100 | 0.319 | | Average Precision (AP) | 0.50:0.95 | small | 100 | -1.000 | | Average Precision (AP) | 0.50:0.95 | medium | 100 | 0.426 | | Average Precision (AP) | 0.50:0.95 | large | 100 | 0.457 | | Average Recall (AR) | 0.50:0.95 | all | 1 | 0.518 | | Average Recall (AR) | 0.50:0.95 | all | 10 | 0.645 | | Average Recall (AR) | 0.50:0.95 | all | 100 | 0.715 | | Average Recall (AR) | 0.50:0.95 | small | 100 | -1.000 | | Average Recall (AR) | 0.50:0.95 | medium | 100 | 0.633 | | Average Recall (AR) | 0.50:0.95 | large | 100 | 0.716 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.1 - Tokenizers 0.13.3