Update min warmup iterations from 1k to 100 (#6768)

train.py

@@ -268,7 +268,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
 
     # Start training
     t0 = time.time()
-    nw = max(round(hyp['warmup_epochs'] * nb), 1000)  # number of warmup iterations, max(3 epochs, 1k iterations)
+    nw = max(round(hyp['warmup_epochs'] * nb), 100)  # number of warmup iterations, max(3 epochs, 100 iterations)
     # nw = min(nw, (epochs - start_epoch) / 2 * nb)  # limit warmup to < 1/2 of training
     last_opt_step = -1
     maps = np.zeros(nc)  # mAP per class