Why does the summaryFunction data only returns 10 rows with custom metric (caret trControl)

I was trying to generate my own F1 metric, however I am wondering why I only get 10 rows for my prediction in the data parameter.

Can somebody please clarify were it doesn't return me all predictions and obs made and how the F1_score is able to predict from 10 rows?

Here they code:

set.seed(346)
dat - twoClassSim(200)

## See https://topepo.github.io/caret/model-training-and-tuning.html#metrics
f1 - function(data, lev = NULL, model = NULL) {
  print(data)
  f1_val - F1_Score(y_pred = data$pred, y_true = data$obs, positive = lev[1])
  acc-confusionMatrix(data$pred,data$obs)
  
  c(F1 = f1_val, ACC = acc$overall['Accuracy'])
}

set.seed(35)
mod - train(Class ~ ., data = dat,
             method = rpart,
             metric = F1,
             trControl = trainControl(summaryFunction = f1, 
                                      classProbs = TRUE))
mod

The data frame that gets returned:

pred.   obs.    Class1.     Class2.     rowIndex
Class2  Class2  0.8014277   0.1985723   54
Class2  Class1  0.4387005   0.5612995   119
Class1  Class1  0.2353023   0.7646977   140
Class2  Class2  0.5893232   0.4106768   172
Class1  Class2  0.6507214   0.3492786   28
Class2  Class1  0.4134056   0.5865944   110
Class2  Class2  0.4729114   0.5270886   40
Class1  Class1  0.6359241   0.3640759   51
Class1  Class2  0.7030223   0.2969777   127
Class1  Class1  0.3007686   0.6992314   72
```