Update README.md

README.md

@@ -3,31 +3,33 @@ license: apache-2.0
 base_model: hustvl/yolos-tiny
 tags:
 - generated_from_trainer
+- Workplace Safety
+- Safety
 datasets:
 - hard-hat-detection
 model-index:
 - name: yolos-tiny-Hard_Hat_Detection
   results: []
+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-tiny-Hard_Hat_Detection
 
 This model is a fine-tuned version of [hustvl/yolos-tiny](https://huggingface.co/hustvl/yolos-tiny) on the hard-hat-detection dataset.
 
 ## 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/Hard%20Hat%20Detection/Hard_Hat_Object_Detection_YOLOS.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/keremberke/hard-hat-detection
 
 ## Training procedure
 
@@ -44,11 +46,24 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-
+| Metric Name | IoU | Area| maxDets | Metric Value |
+|:-----:|:-----:|:-----:|:-----:|:-----:|
+| Average Precision (AP)| IoU=0.50:0.95 | all | maxDets=100 | 0.346 |
+| Average Precision (AP)| IoU=0.50 | all | maxDets=100 | 0.747 |
+| Average Precision (AP)| IoU=0.75 | all | maxDets=100 | 0.275 |
+| Average Precision (AP)| IoU=0.50:0.95 | small | maxDets=100 | 0.128 |
+| Average Precision (AP)| IoU=0.50:0.95 | medium | maxDets=100 | 0.343 |
+| Average Precision (AP)| IoU=0.50:0.95 | large | maxDets=100 | 0.521 |
+| Average Recall (AR)| IoU=0.50:0.95 | all | maxDets=1 | 0.188 |
+| Average Recall (AR)| IoU=0.50:0.95 | all | maxDets=10 |  0.484 |
+| Average Recall (AR)| IoU=0.50:0.95 | all | maxDets=100 | 0.558 |
+| Average Recall (AR)| IoU=0.50:0.95 | small | maxDets=100 | 0.320 |
+| Average Recall (AR)| IoU=0.50:0.95 | medium | maxDets=100 | 0.538 |
+| Average Recall (AR)| IoU=0.50:0.95 | large | maxDets=100 | 0.743 |
 
 ### Framework versions
 
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.3
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3