diff --git a/train.py b/train.py
index 293db6b9..182d7dca 100644
--- a/train.py
+++ b/train.py
@@ -240,7 +240,7 @@ def train(
         if not (opt.notest or (opt.nosave and epoch < 10)) or epoch == epochs - 1:
             with torch.no_grad():
                 results, maps = test.test(cfg, data_cfg, batch_size=batch_size, img_size=opt.img_size, model=model,
-                                          conf_thres=0.1)
+                                          conf_thres=0.001)
 
         # Write epoch results
         with open('results.txt', 'a') as file:
@@ -348,14 +348,14 @@ if __name__ == '__main__':
 
             # Mutate
             init_seeds(seed=int(time.time()))
-            s = [.15, .15, .15, .15, .15, .15, .15, .15, .10, .10, .10, .10]  # fractional sigmas
+            s = [.15, .15, .15, .15, .15, .15, .15, .15, .15, .00, .05, .10]  # fractional sigmas
             for i, k in enumerate(hyp.keys()):
                 x = (np.random.randn(1) * s[i] + 1) ** 2.0  # plt.hist(x.ravel(), 300)
                 hyp[k] *= float(x)  # vary by 20% 1sigma
 
             # Clip to limits
             keys = ['lr0', 'iou_t', 'momentum', 'weight_decay']
-            limits = [(1e-4, 1e-2), (0.00, 0.70), (0.60, 0.98), (0, 0.01)]
+            limits = [(1e-4, 1e-2), (0.00, 0.70), (0.60, 0.95), (0, 0.01)]
             for k, v in zip(keys, limits):
                 hyp[k] = np.clip(hyp[k], v[0], v[1])