msmarco-v2-passage-d2q-t5.template

# Anserini Regressions: MS MARCO (V2) Passage Ranking

**Models**: BM25 with doc2query-T5 expansions on original passages

This page describes regression experiments for passage ranking on the MS MARCO V2 passage corpus using the dev queries, which is integrated into Anserini's regression testing framework.
Here, we expand the passage corpus with doc2query-T5.
For additional instructions on working with the MS MARCO V2 passage corpus, refer to [this page](${root_path}/docs/experiments-msmarco-v2.md).

The exact configurations for these regressions are stored in [this YAML file](${yaml}).
Note that this page is automatically generated from [this template](${template}) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.

From one of our Waterloo servers (e.g., `orca`), the following command will perform the complete regression, end to end:

```
python src/main/python/run_regression.py --index --verify --search --regression ${test_name}
```

## Indexing

Typical indexing command:

```
${index_cmds}
```

The directory `/path/to/msmarco-v2-passage-d2q-t5/` should be a directory containing the compressed `jsonl` files that comprise the corpus.

For additional details, see explanation of [common indexing options](${root_path}/docs/common-indexing-options.md).

## Retrieval

Topics and qrels are stored [here](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels), which is linked to the Anserini repo as a submodule.

After indexing has completed, you should be able to perform retrieval as follows:

```
${ranking_cmds}
```

Evaluation can be performed using `trec_eval`:

```
${eval_cmds}
```

## Effectiveness

With the above commands, you should be able to reproduce the following results:

${effectiveness}