update docs on residual
@@ -67,7 +67,9 @@ The base model was trained for 200 epochs on 8 GPUs. We use:
* dropout (varible per layer: 0.2-0.4)
* batch size of 32 per GPU for float32 and 64 for mixed-precision.
-The xlarge models are trained for 400 epochs on 8 GPUs. All other parameters are kept the same as the base model.
+The xlarge models are trained for 400 epochs on 8 GPUs. All other parameters are kept the same as the base model except:
+
+* we add residual connections between each convolutional block
Mixed Precision
