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--- pipeline:window:cryolo:picking_general_refine [2019/09/18 10:36]
twagner [Picking particles - Using the general model refined for your data]
+++ pipeline:window:cryolo:picking_general_refine [2019/09/18 10:39]
twagner [4. Training]
@@ Line 13: / Line 13: @@
   - The training will need less GPU memory ((We are testing crYOLO with its default configuration on graphic cards with >= 8 GB memory. Using the fine tune mode, it should also work with GPUs with 4 GB memory)) and therefore is usable with NVIDIA cards with less memory.
-However, the fine tune mode is still somewhat experimental and we will update this section if see more advantages or disadvantages.
+However, the fine tune mode is still somewhat experimental and we will update this section as crYOLO develops over time.
 If you followed the installation instructions, you now have to activate the cryolo virtual environment with
@@ Line 76: / Line 76: @@
 {{ :pipeline:window:cryolo_refine_02.png?300 |}}
 <note important>
-The number of layers to fine tune (specified by layers_fine_tune in the //"Optional arguments"// tab) is still experimental. The default value of 2 worked for us but you might need more layers..
+The number of layers to fine tune (specified by layers_fine_tune in the //"Optional arguments"// tab) is still experimental. The default value of 2 worked for us but you might need more layers.
 </note>
@@ Line 94: / Line 94: @@
-<hidden **Run training with the command line**>
+<hidden **Alternative:** Run training with the command line>
 In comparison to the training from scratch, you can skip the warm up training ( -w 0 ). Moreover you have to add the //%%--%%fine_tune// flag to tell crYOLO that it should do fine tuning. You can also tell crYOLO how many layers it should fine tune (default is two layers with -lft 2 ):

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