msmarco-doc.template

# Anserini: Regressions for [MS MARCO (Document)](https://github.com/microsoft/TREC-2019-Deep-Learning)

This page documents regression experiments for the MS MARCO Document Ranking Task, which is integrated into Anserini's regression testing framework.
For more complete instructions on how to run end-to-end experiments, refer to [this page](experiments-msmarco-doc.md).

The exact configurations for these regressions are stored in [this YAML file](../src/main/resources/regression/msmarco-doc.yaml).
Note that this page is automatically generated from [this template](../src/main/resources/docgen/templates/msmarco-doc.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.

## Indexing

Typical indexing command:

```
${index_cmds}
```

The directory `/path/to/msmarco-doc/` should be a directory containing the official document collection (a single file), in TREC format.

For additional details, see explanation of [common indexing options](common-indexing-options.md).

## Retrieval

Topics and qrels are stored in [`src/main/resources/topics-and-qrels/`](../src/main/resources/topics-and-qrels/).
The regression experiments here evaluate on the 5193 dev set questions; see [this page](experiments-msmarco-doc.md) for more details.

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 replicate the following results:

${effectiveness}

The setting "default" refers the default BM25 settings of `k1=0.9`, `b=0.4`, while "tuned" refers to the tuned setting of `k1=3.44`, `b=0.87`.
See [this page](experiments-msmarco-doc.md) for more details.
Note that here we are using `trec_eval` to evaluate the top 1000 hits for each query; beware, the runs provided by MS MARCO organizers for reranking have only 100 hits per query.