diff --git a/train.py b/train.py
index 4d06ce1..1949fc8 100644
--- a/train.py
+++ b/train.py
@@ -178,12 +178,12 @@ def set_args_12gb(args):
     if not args.gradient_checkpointing:   
         logging.info("  - Overiding gradient checkpointing to True")
         args.gradient_checkpointing = True
-    if args.batch_size != 1:
-        logging.info("  - Overiding batch size to 1")
-        args.batch_size = 1
+    if args.batch_size > 2:
+        logging.info("  - Overiding batch size to max 2")
+        args.batch_size = 2
         args.grad_accum = 1
     if args.resolution > 512:
-        logging.info("  - Overiding resolution to 512")
+        logging.info("  - Overiding resolution to max 512")
         args.resolution = 512
 
 def find_last_checkpoint(logdir):
@@ -214,6 +214,12 @@ def setup_args(args):
     Sets defaults for missing args (possible if missing from json config)
     Forces some args to be set based on others for compatibility reasons
     """
+    if args.disable_amp:
+        logging.warning(f"{Fore.LIGHTYELLOW_EX} Disabling AMP, not recommended.{Style.RESET_ALL}")
+        args.amp= False
+    else:
+        args.amp = True
+
     if args.disable_unet_training and args.disable_textenc_training:
         raise ValueError("Both unet and textenc are disabled, nothing to train")
 
@@ -939,13 +945,14 @@ if __name__ == "__main__":
         print("No config file specified, using command line args")
 
     argparser = argparse.ArgumentParser(description="EveryDream2 Training options")
-    argparser.add_argument("--amp", action="store_true", default=False, help="Enables automatic mixed precision compute, recommended on")
+    argparser.add_argument("--amp", action="store_true",  default=False, help="deprecated, use --disable_amp if you wish to disable AMP")
     argparser.add_argument("--batch_size", type=int, default=2, help="Batch size (def: 2)")
     argparser.add_argument("--ckpt_every_n_minutes", type=int, default=None, help="Save checkpoint every n minutes, def: 20")
     argparser.add_argument("--clip_grad_norm", type=float, default=None, help="Clip gradient norm (def: disabled) (ex: 1.5), useful if loss=nan?")
     argparser.add_argument("--clip_skip", type=int, default=0, help="Train using penultimate layer (def: 0) (2 is 'penultimate')", choices=[0, 1, 2, 3, 4])
     argparser.add_argument("--cond_dropout", type=float, default=0.04, help="Conditional drop out as decimal 0.0-1.0, see docs for more info (def: 0.04)")
     argparser.add_argument("--data_root", type=str, default="input", help="folder where your training images are")
+    argparser.add_argument("--disable_amp", action="store_true", default=False, help="disables training of text encoder (def: False)")
     argparser.add_argument("--disable_textenc_training", action="store_true", default=False, help="disables training of text encoder (def: False)")
     argparser.add_argument("--disable_unet_training", action="store_true", default=False, help="disables training of unet (def: False) NOT RECOMMENDED")
     argparser.add_argument("--disable_xformers", action="store_true", default=False, help="disable xformers, may reduce performance (def: False)")