Table 2.
Means of metrics of ten individual Zoobot fine-tuning runs, assuming a complete binary class split (non-merger class (class 0): merger probability < 0.5, merger class (class 1): merger probability > 0.5).
| Class | Precision | Recall | F1-Score |
|---|---|---|---|
| Non-merger | 0.74 | 0.83 | 0.75 |
| Merger | 0.80 | 0.70 | 0.80 |
Notes. Each run split the TNG50 data-set into different 63% training, 27% validation, and 10% testing data-sets. The metrics are based on the validation data-set.
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