diff --git a/train.py b/train.py
index ff02e154..4f96e291 100644
--- a/train.py
+++ b/train.py
@@ -417,10 +417,10 @@ def prebias():
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--epochs', type=int, default=273)  # 500200 batches at bs 16, 117263 images = 273 epochs
-    parser.add_argument('--batch-size', type=int, default=16)  # effective bs = batch_size * accumulate = 16 * 4 = 64
+    parser.add_argument('--batch-size', type=int, default=1)  # effective bs = batch_size * accumulate = 16 * 4 = 64
     parser.add_argument('--accumulate', type=int, default=4, help='batches to accumulate before optimizing')
     parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
-    parser.add_argument('--data', type=str, default='data/coco.data', help='*.data file path')
+    parser.add_argument('--data', type=str, default='data/coco_64img.data', help='*.data file path')
     parser.add_argument('--multi-scale', action='store_true', help='adjust (67% - 150%) img_size every 10 batches')
     parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
     parser.add_argument('--rect', action='store_true', help='rectangular training')
diff --git a/utils/gcp.sh b/utils/gcp.sh
index f39d3a64..c898ab60 100755
--- a/utils/gcp.sh
+++ b/utils/gcp.sh
@@ -4,10 +4,10 @@
 rm -rf sample_data yolov3 darknet apex coco cocoapi knife knifec
 git clone https://github.com/ultralytics/yolov3
 git clone https://github.com/NVIDIA/apex && cd apex && pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" . --user && cd .. && rm -rf apex
-conda install -yc conda-forge scikit-image pycocotools
+sudo conda install -yc conda-forge scikit-image pycocotools
 python3 -c "
 from yolov3.utils.google_utils import gdrive_download
-gdrive_download('1HaXkef9z6y5l4vUnCYgdmEAj61c6bfWO','coco.zip')"
+gdrive_download('1WQT6SOktSe8Uw6r10-2JhbEhMY5DJaph','coco.zip')"
 sudo shutdown
 
 # Re-clone