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                                            Tim Koornstra

How to log F1, precision, recall and other custom metrics while training apart from training and validation loss

I did it like this: ```py from somewhere import val_ds _PRF_RE = re.compile(r"P:\s*([\d.,]+)%.*?R:\s*([\d.,]+)%.*?F1:\s*([\d.,]+)%", re.S) def compute_metrics(_eval_pred): output, f1 = model.evaluate( val_ds.data, threshold=0.5, flat_ner=True, batch_size=1, ) m = _PRF_RE.search(output) if m:...