modified the total epochs

main.py

@@ -15,7 +15,7 @@
 parser = argparse.ArgumentParser(description='PyTorch Super Res Example')
 parser.add_argument('--batchSize', type=int, default=125, help='training batch size')
 parser.add_argument('--testBatchSize', type=int, default=10, help='testing batch size')
-parser.add_argument('--nEpochs', type=int, default=1000, help='number of epochs to train for')
+parser.add_argument('--nEpochs', type=int, default=600, help='number of epochs to train for')
 parser.add_argument('--lr', type=float, default=0.01, help='Learning Rate. Default=0.01')
 parser.add_argument('--cuda', action='store_true', help='use cuda?')
 parser.add_argument('--threads', type=int, default=4, help='number of threads for data loader to use')
@@ -24,7 +24,7 @@
 parser.add_argument("--resume", default="", type=str, help="Path to checkpoint (default: none)")
 parser.add_argument("--start-epoch", default=1, type=int, help="Manual epoch number (useful on restarts)")
 parser.add_argument("--pretrained", default="", type=str, help="path to pretrained model (default: none)")
-parser.add_argument("--step", type=int, default=100, help="Sets the learning rate to the initial LR decayed by momentum every n epochs, Default: n=500")
+parser.add_argument("--step", type=int, default=150, help="Sets the learning rate to the initial LR decayed by momentum every n epochs, Default: n=500")
 opt = parser.parse_args()
 
 def main():
@@ -118,7 +118,7 @@ def train(training_data_loader, optimizer, model, criterion, epoch):
                                                                 loss.data[0]))
 
 def save_checkpoint(model, epoch):
-    model_out_path = "model/" + "model_epoch_{}.pth".format(epoch)
+    model_out_path = "model/model" + "model_epoch_{}.pth".format(epoch)
     state = {"epoch": epoch, "model": model}
 
     if not os.path.exists("model/"):