Improve wording in train parameter description

Co-authored-by: Jacob Sznajdman <breakanalysis@gmail.com>

Author: FlorentinD

doc/asciidoc/machine-learning/node-embeddings/graph-sage/specific-train-configuration.adoc

@@ -10,10 +10,10 @@
 | sampleSizes                                                                      | List of Integer | [25, 10]  | yes      | A list of Integer values, the size of the list determines the number of layers and the values determine how many nodes will be sampled by the layers.
 | projectedFeatureDimension                                                        | Integer       | n/a       | yes      | The dimension of the projected `featureProperties`. This enables multi-label GraphSage, where each label can have a subset of the `featureProperties`.
 | batchSize                                                                        | Integer       | 100       | yes      | The number of nodes per batch.
-| <<common-configuration-tolerance,tolerance>>                                     | Float         | 1e-4      | yes      | Tolerance used for the early convergence of an epoch.
+| <<common-configuration-tolerance,tolerance>>                                     | Float         | 1e-4      | yes      | Tolerance used for the early convergence of an epoch, which is checked after each iteration.
 | learningRate                                                                     | Float         | 0.1       | yes      | The learning rate determines the step size at each iteration while moving toward a minimum of a loss function.
 | epochs                                                                           | Integer       | 1         | yes      | Number of times to traverse the graph.
-| <<common-configuration-max-iterations,maxIterations>>                            | Integer       | 10        | yes      | Maximum number of weight updates per batch. Batches can also converge early based on `tolerance`.
+| <<common-configuration-max-iterations,maxIterations>>                            | Integer       | 10        | yes      | Maximum number of iterations per epoch. Each iteration the weights are updated.
 | searchDepth                                                                      | Integer       | 5         | yes      | Maximum depth of the RandomWalks to sample nearby nodes for the training.
 | negativeSampleWeight                                                             | Integer       | 20        | yes      | The weight of the negative samples. Higher values increase the impact of negative samples in the loss.
 | <<common-configuration-relationship-weight-property,relationshipWeightProperty>> | String        | null      | yes      | Name of the relationship property to use as weights. If unspecified, the algorithm runs unweighted.