diff --git a/README.md b/README.md
index c0bc8cbc..539373b5 100755
--- a/README.md
+++ b/README.md
@@ -140,10 +140,10 @@ Success: converted 'weights/yolov3-spp.pt' to 'converted.weights'
|Size |COCO mAP
@0.5...0.95 |COCO mAP
@0.5
--- | --- | --- | ---
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0
28.7
30.5
**37.0** |29.1
51.8
52.3
**56.0**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**40.7** |33.0
55.4
56.9
**60.4**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**42.0** |34.9
57.7
59.5
**61.9**
-YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**42.4** |35.4
58.2
60.7
**62.0**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0
28.7
30.5
**37.5** |29.1
51.8
52.3
**56.8**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**41.1** |33.0
55.4
56.9
**60.6**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**42.6** |34.9
57.7
59.5
**62.3**
+YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**42.8** |35.4
58.2
60.7
**62.5**
- mAP@0.5 run at `--iou-thr 0.5`, mAP@0.5...0.95 run at `--iou-thr 0.7`
- Darknet results: https://arxiv.org/abs/1804.02767
@@ -155,20 +155,20 @@ Namespace(augment=True, batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.00
Using CUDA device0 _CudaDeviceProperties(name='Tesla V100-SXM2-16GB', total_memory=16130MB)
Class Images Targets P R mAP@0.5 F1: 100%|█████████| 313/313 [03:00<00:00, 1.74it/s]
- all 5e+03 3.51e+04 0.396 0.731 0.634 0.509
+ all 5e+03 3.51e+04 0.372 0.743 0.636 0.49
- Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.447
- Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.641
- Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.485
- Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.271
- Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.492
- Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.583
- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.357
- 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 ] = 0.652
- Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.488
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.450
+ Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.643
+ Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.486
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.265
+ Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.498
+ Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.577
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.361
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.593
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.654
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.486
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.701
- Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.787
+ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.804
Speed: 21.3/3.0/24.4 ms inference/NMS/total per 640x640 image at batch-size 16
```