Update README.md

README.md

@@ -19,19 +19,19 @@ YOLOS model fine-tuned on COCO 2017 object detection (118k annotated images). It
 This [hustvl/yolos-small](https://huggingface.co/hustvl/yolos-small) model has been finetuned on these two datasets[[1](https://universe.roboflow.com/new-workspace-phqon/object-detection-brcrx)][[2](https://universe.roboflow.com/tank-detect/person-dataset-kzsop)] (2604 samples) with the following results on the test set:
 
 ```
- IoU metric: bbox
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.472
- Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.856
- Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.494
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.029
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.420
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.633
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.381
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.587
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.662
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.157
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.647
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.775
+IoU metric: bbox
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.501
+ Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.866
+ Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.498
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.048
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.455
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.648
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.412
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.601
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.632
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.224
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.600
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.756
 ```
 
 ## How to use
@@ -70,8 +70,8 @@ This model is more of an experiment on a small scale and will need retraining on
 
 The following hyperparameters were used during training:
 - learning_rate: 3e-05
-- train_batch_size: 2
-- eval_batch_size: 2
+- train_batch_size: 4
+- eval_batch_size: 4
 - seed: 42
 - optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
 - num_epochs: 5