ML MCONF NEW: Difference between revisions
(Documented that increasing the parameter for ML_ISTART=3 increases efficiency.) |
No edit summary |
||
| (4 intermediate revisions by 2 users not shown) | |||
| Line 7: | Line 7: | ||
The use of this tag in combination with the learning algorithms is described here: [[Machine learning force field calculations: Basics#Sampling of training data and local reference configurations|here]]. | The use of this tag in combination with the learning algorithms is described here: [[Machine learning force field calculations: Basics#Sampling of training data and local reference configurations|here]]. | ||
If force fields are reparameterized ({{ | If force fields are reparameterized ({{TAGO|ML_MODE|select}}), calculations are usually more efficient if this parameter is increased to values around 10-16 and setting {{TAGO|ML_CDOUB|4}}. This is particularly relevant if the ML_AB file is large. | ||
== Related tags and articles == | == Related tags and articles == | ||
Latest revision as of 15:32, 19 October 2023
ML_MCONF_NEW = [integer]
Default: ML_MCONF_NEW = 5
Description: This tag sets the number of configurations that are stored temporarily as candidates for the training data in the machine learning force field method.
| Warning: This value is close to optimal for on-the-fly learning, and should usually not be changed. |
The use of this tag in combination with the learning algorithms is described here: here.
If force fields are reparameterized (ML_MODE = select), calculations are usually more efficient if this parameter is increased to values around 10-16 and setting ML_CDOUB = 4. This is particularly relevant if the ML_AB file is large.