Update README.md

README.md

@@ -8,26 +8,26 @@ datasets:
 model-index:
 - name: yolos-small-Forklift_Object_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-small-Forklift_Object_Detection
 
 This model is a fine-tuned version of [hustvl/yolos-small](https://huggingface.co/hustvl/yolos-small) on the forklift-object-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/tree/main/Computer%20Vision/Object%20Detection/Forklift%20Object%20Detection
 
 ## 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/forklift-object-detection
 
 ## Training procedure
 
@@ -44,11 +44,24 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-
+| Metric Name | IoU | Area Category | maxDets | Metric Value |
+|:-----:|:-----:|:-----:|:-----:|:-----:|
+| Average Precision  (AP) | IoU=0.50:0.95 | area=   all | maxDets=100 | 0.136 |
+| Average Precision  (AP) | IoU=0.50      | area=   all | maxDets=100 | 0.400 |
+| Average Precision  (AP) | IoU=0.75      | area=   all | maxDets=100 | 0.054 |
+| 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 | 0.051 |
+| Average Precision  (AP) | IoU=0.50:0.95 | area= large | maxDets=100 | 0.177 |
+| Average Recall     (AR) | IoU=0.50:0.95 | area=   all | maxDets=  1 | 0.178 |
+| Average Recall     (AR) | IoU=0.50:0.95 | area=   all | maxDets= 10 | 0.294 |
+| Average Recall     (AR) | IoU=0.50:0.95 | area=   all | maxDets=100 | 0.340 |
+| Average Recall     (AR) | IoU=0.50:0.95 | area= small | maxDets=100 | 0.075 |
+| Average Recall     (AR) | IoU=0.50:0.95 | area=medium | maxDets=100 | 0.299 |
+| Average Recall     (AR) | IoU=0.50:0.95 | area= large | maxDets=100 | 0.373 |
 
 ### Framework versions
 
 - Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.3
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3