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fix: evaluate missing splits #1268
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fix: evaluate missing splits #1268
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@thivyanth Thanks for taking a first stab at it! For any new functionality, we usually add a test / test cases to help confirm that the added code works. Could you please add a test for this? Specifically the following cases:
- Results exist, but no missing splits
- Results exist, and 1 missing split.
I can review the PR afterwards.
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Looking good, but still a few things to adjust.
mteb/evaluation/MTEB.py
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if save_path.exists() and not overwrite_results: | ||
logger.info( | ||
f"{task.metadata.name} results already exists. Loading results from disk. Set overwrite_results=True to overwrite." | ||
existing_results = self.load_existing_results(save_path) |
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you should use
MTEBResults.from_disk(path)
to load results.
(see line 354)
mteb/evaluation/MTEB.py
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logger.info( | ||
f"{task.metadata.name} results exist but missing splits: {missing_splits}. Running evaluation for missing splits." | ||
) | ||
task_eval_splits = missing_splits |
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This will overwrite the existing file further down resulting in a new file where the splits are missing. You will have to merge the results objects.
mteb/evaluation/MTEB.py
Outdated
def compare_splits_and_subsets(self, existing_results, task_eval_splits): | ||
missing_splits = [] | ||
for split in task_eval_splits: | ||
if split not in existing_results: | ||
missing_splits.append(split) | ||
return missing_splits |
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def compare_splits_and_subsets(self, existing_results, task_eval_splits): | |
missing_splits = [] | |
for split in task_eval_splits: | |
if split not in existing_results: | |
missing_splits.append(split) | |
return missing_splits | |
@staticmethod | |
def compare_splits_and_subsets(existing_results: MTEBResults, task_eval_splits: list[str]) -> list[str]: | |
missing_splits = [] | |
for split in task_eval_splits: # this will need to be adapted to MTEBResults object | |
if split not in existing_results: | |
missing_splits.append(split) | |
return missing_splits |
@KennethEnevoldsen Thank you for the suggestions. I've implemented the changes as requested but from scratch. I manually checked the logs to ensure that only the missing splits are being evaluated rather than running a pytest. Could you please suggest a way to verify this with pytest, specifically to confirm that only the missing splits are evaluated? @isaac-chung @Muennighoff (The latest commit has passed make test and make lint.) |
Wrote a test as well. (The latest commit has passed make test and make lint.) |
@thivyanth rerunning failed test to ensure that everything passes |
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This is already looking much better - A few more changes are needed though, let me know if there are any questions
self.last_evaluated_splits[task.metadata_dict["name"]] = set() | ||
self.last_evaluated_splits[task.metadata_dict["name"]].add(split) | ||
|
||
new_results = MTEBResults.from_task_results( |
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We need to consider what to do with the MTEB version specification.
Ideally we should add multiple "1.2.11, 1.2.16". We should also add a flag to only append to existing files if the version matches (should probably be on by default)
f"{task.metadata.name} results already exist. Loading results from disk." | ||
) | ||
evaluation_results.append(existing_results) | ||
self.last_evaluated_splits[task.metadata.name] = [] # Add this line |
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Seems like an error?
@@ -488,3 +563,11 @@ def _save_model_metadata(model_meta: ModelMeta, output_folder: Path) -> None: | |||
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|||
with save_path.open("w") as f: | |||
json.dump(model_meta.to_dict(), f) | |||
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|||
def get_last_evaluated_splits(self): |
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Is this needed? (I would just add some logging messages instead)
if existing_results: | ||
merged_results = self._merge_results(existing_results, new_results) |
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probably worth merging using the MTEBResult object, instead of directly on the dict.
new_results = MTEBResults(...)
if existing_results:
new_results.update(existing_results)
@pytest.fixture | ||
def model(): | ||
return SentenceTransformer("all-MiniLM-L6-v2") |
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Use mock model instead (see e.g. MockNumpyEncoder here)
@pytest.fixture | ||
def nfcorpus_tasks(): | ||
return mteb.get_tasks(tasks=["NFCorpus"], languages=["eng"]) |
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Use MockTask as well (see above)
evaluation.run( | ||
model, | ||
eval_splits=["train", "test"], | ||
save_predictions=True, | ||
output_folder=str(tmp_path / "testcase1"), | ||
verbosity=2, | ||
) | ||
last_evaluated_splits = evaluation.get_last_evaluated_splits() | ||
print(last_evaluated_splits) | ||
assert "NFCorpus" in last_evaluated_splits | ||
assert set(last_evaluated_splits["NFCorpus"]) == {"train", "test"} | ||
assert len(last_evaluated_splits["NFCorpus"]) == 2 |
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We can simplify tests a bit: (general across tests)
evaluation.run( | |
model, | |
eval_splits=["train", "test"], | |
save_predictions=True, | |
output_folder=str(tmp_path / "testcase1"), | |
verbosity=2, | |
) | |
last_evaluated_splits = evaluation.get_last_evaluated_splits() | |
print(last_evaluated_splits) | |
assert "NFCorpus" in last_evaluated_splits | |
assert set(last_evaluated_splits["NFCorpus"]) == {"train", "test"} | |
assert len(last_evaluated_splits["NFCorpus"]) == 2 | |
result_obj = evaluation.run( | |
model, | |
eval_splits=["train", "test"], | |
save_predictions=True, | |
output_folder=str(tmp_path / "testcase1"), | |
verbosity=2, | |
) | |
# check splits here based on object - no need to last_evaluated_splits |
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any reason why save_predictions is true?
@thivyanth great work thus far! It's a pretty useful PR so would be amazing to have it merged soon if you have time to address the comments? |
I just saw this message, few hours ago I had mailed you |
Any update here @thivyanth? Would be great to get this in! 🙌 |
@thivyanth would love to get this merged in. Do you still have time to work on it? |
Addresses #1260
Checklist
@Muennighoff @isaac-chung
make test
.944 passed, 236 skipped, 55 warnings in 232.13s (0:03:52)
make lint
.