use in1k pretrained for coco

yolo/engine.py

@@ -62,7 +62,7 @@ class YoloTrainer(object):
         self.scaler = torch.cuda.amp.GradScaler(enabled=args.fp16)
 
         # ---------------------------- Build Optimizer ----------------------------
-        self.grad_accumulate = max(64 // args.batch_size, 1)
+        self.grad_accumulate = max(256 // args.batch_size, 1)
         cfg.base_lr = cfg.per_image_lr * args.batch_size * self.grad_accumulate
         cfg.min_lr  = cfg.base_lr * cfg.min_lr_ratio
         self.optimizer, self.start_epoch = build_yolo_optimizer(cfg, model, args.resume)