Update hyper-parameters for mobilenetV2 object detection task with QAT.

PiperOrigin-RevId: 465124474

official/projects/qat/vision/configs/experiments/retinanet/coco_mobilenetv2_qat_tpu_e2e.yaml

 # --experiment_type=retinanet_spinenet_mobile_coco_qat
-# COCO mAP: 18.4 (Evaluated on the TFLite after conversion.)
+# COCO mAP: 21.62 (Evaluated on the TFLite after conversion.)
 # QAT only supports float32 tpu due to fake-quant op.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'float32'
 task:
   losses:
-    l2_weight_decay: 3.0e-05
+    l2_weight_decay: 3.0e-04
   model:
     anchor:
       anchor_size: 3
@@ -45,7 +45,7 @@ task:
       aug_scale_min: 0.5
   validation_data:
     dtype: 'float32'
-    global_batch_size: 16
+    global_batch_size: 64
     is_training: false
   quantization:
     pretrained_original_checkpoint: 'gs://**/tf2_mobilenetv2_ssd_jul29/28129005/ckpt-277200'
@@ -54,15 +54,15 @@ task:
 trainer:
   optimizer_config:
     learning_rate:
-      stepwise:
-        boundaries: [263340, 272580]
-        values: [0.032, 0.0032, 0.00032]
-      type: 'stepwise'
-    warmup:
-      linear:
-        warmup_learning_rate: 0.00067
-        warmup_steps: 2000
+      type: 'exponential'
+      exponential:
+        decay_rate: 0.96
+        decay_steps: 231
+        initial_learning_rate: 0.2
+        name: 'ExponentialDecay'
+        offset: 0
+        staircase: true
   steps_per_loop: 462
-  train_steps: 277200
+  train_steps: 46200
   validation_interval: 462
   validation_steps: 625