[image] update readme for the resnet example (#132)

image/resnet/README.md

@@ -1,4 +1,4 @@
-# Train ResNet34 on CIFAR10
+# Train ResNet on CIFAR10
 
 ## Prepare Dataset
 
@@ -12,7 +12,7 @@ export DATA=/path/to/data
 
 ## Run single-GPU training
 
-We provide two examples of training resnet 18 on the CIFAR10 dataset. 
+We provide two examples of training resnet 18 on the CIFAR10 dataset. You can choose other ResNet models in `resnet.py` as well.
 You can change the value of `nproc_per_node` to adjust the number of GPUs used for training. 
 When the `nproc_per_node` is changed, you may need to adjust the learning rate and batch size in the `config.py` accordingly.
 Normally we follow the rule of linear scaling, which is `new_global_batch_size / new_learning_rate = old_global_batch_size / old_learning rate`.