Update README.md

README.md

@@ -6,26 +6,28 @@ tags:
 model-index:
 - name: yolos-small-Cell_Tower_Detection
   results: []
+datasets:
+- Francesco/cell-towers
+language:
+- en
+pipeline_tag: object-detection
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # yolos-small-Cell_Tower_Detection
 
-This model is a fine-tuned version of [hustvl/yolos-small](https://huggingface.co/hustvl/yolos-small) on an unknown dataset.
+This model is a fine-tuned version of [hustvl/yolos-small](https://huggingface.co/hustvl/yolos-small).
 
 ## Model description
 
-More information needed
+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/Cell%20Tower%20Object%20Detection/Cell%20Tower%20Detection%20YOLOS.ipynb
 
 ## Intended uses & limitations
 
-More information needed
+This model is intended to demonstrate my ability to solve a complex problem using technology.
 
 ## Training and evaluation data
 
-More information needed
+Dataset Source: https://huggingface.co/datasets/Francesco/cell-towers
 
 ## Training procedure
 
@@ -42,11 +44,24 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-
+| Metric Name | IoU | Area | maxDets | Metric Value |
+|:-----:|:-----:|:-----:|:-----:|:-----:|
+| Average Precision (AP) | IoU=0.50:0.95 | area=   all | maxDets=100 | 0.287 |
+| Average Precision (AP) | IoU=0.50      | area=   all | maxDets=100 | 0.636 |
+| Average Precision (AP) | IoU=0.75      | area=   all | maxDets=100 | 0.239 |
+| Average Precision (AP) | IoU=0.50:0.95 | area= small | maxDets=100 | 0.069 |
+| Average Precision (AP) | IoU=0.50:0.95 | area=medium | maxDets=100 | 0.289 |
+| Average Precision (AP) | IoU=0.50:0.95 | area= large | maxDets=100 | 0.556 |
+| Average Recall (AR) | IoU=0.50:0.95 | area=   all | maxDets=  1 | 0.192 |
+| Average Recall (AR) | IoU=0.50:0.95 | area=   all | maxDets= 10 | 0.460 |
+| Average Recall (AR) | IoU=0.50:0.95 | area=   all | maxDets=100 | 0.492 |
+| Average Recall (AR) | IoU=0.50:0.95 | area= small | maxDets=100 | 0.151 |
+| Average Recall (AR) | IoU=0.50:0.95 | area=medium | maxDets=100 | 0.488 |
+| Average Recall (AR) | IoU=0.50:0.95 | area= large | maxDets=100 | 0.760 |
 
 ### Framework versions
 
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.4
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3