RerankingEvaluator does not write the csv file when the backward compatible `fit()` method is used. Possible fix suggested.

[bluebalam]

• sentence-transformers version tested: 3.3 (branch: 3.3-release)

• Context: we are migrating a production pipeline that fine-tunes a model from sentence-transformers 2.x to 3.x

• In 2.x we used the now deprecated method model.fit() as step toward 3.x we tested the fit() method provided for backward compatibility. However, a RerankingEvaluator we pass during training does not write the csv file with the metrics, as it did before. This file is very useful to us.

• Below my notes on the issue.

RerankingEvaluator needs the output_path to be set in order to write the csv file:

sentence-transformers/sentence_transformers/evaluation/RerankingEvaluator.py

Line 138 in ea49e01

if output_path is not None and self.write_csv:

However, if my understanding is correct, in the fit_mixin.py the class EvaluatorCallback calls the evaluator without passing the output_path :

sentence-transformers/sentence_transformers/fit_mixin.py

Line 117 in ea49e01

evaluator_metrics = self.evaluator(model, epoch=state.epoch)

which causes that the file is not written to disk since output_path is None. Note that the flag write_csv: bool is by default set to True, which is the other condition for the RerankingEvaluator to dump the file:

sentence-transformers/sentence_transformers/evaluation/RerankingEvaluator.py

Line 138 in ea49e01

if output_path is not None and self.write_csv:

.

I think a possible fix would be to modify the call to the evaluator in fit_mixin.py from

evaluator_metrics = self.evaluator(model, epoch=state.epoch)

to

evaluator_metrics = self.evaluator(model, epoch=state.epoch, output_path=args.output_dir)

I do understand this method is provided only to support the transition and it will be removed, but I think it would be nice to have it working as expected in the meantime :) .

[tomaarsen]

Hello!

I do understand this method is provided only to support the transition and it will be removed, but I think it would be nice to have it working as expected in the meantime :) .

I totally agree, there's a good reason that I added the fit() backwards compatibility support, specifically for cases like yours where people transition from 2.x to 3.x. I obviously do recommend eventually switching to the new Trainer - it's simply more powerful, but I'll try and fix this.

I believe your proposed fix does not work equivalently as before, because the output_dir in the args is set to checkpoint_path rather than the provided output_path. I see that the old model.fit() created an eval folder under the output_path and used that as the output_path in the evaluator.

• Tom Aarsen