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# Anserini Regressions: QA with wikipedia-dpr-100w Corpus

**Models**: BM25

This page documents QA regression experiments on the wikipedia-dpr-100w corpus, which is integrated into Anserini's regression testing framework.

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:

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

## Indexing

Typical indexing command:

```bash
${index_cmds}
```

The directory `/path/to/${corpus}/`should be a directory containing the wikipedia-dpr-100w passages collection retrieved from [here](https://dl.fbaipublicfiles.com/dpr/wikipedia_split/psgs_w100.tsv.gz).

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

## Retrieval

Topics are stored in [`src/main/resources/topics-and-qrels/`](../src/main/resources/topics-and-qrels/).
The regression experiments here evaluate on the test set of multiple QA datasets, namely Natural Questions, TriviaQA, SQuAD, and WebQuestions.

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

```bash
${ranking_cmds}
```

The trec format will need to be converted to DPR's JSON format for evaluation:
```bash
${converting_cmds}
```

Evaluation can be performed using scripts from pyserini:

```bash
${eval_cmds}
```

## Effectiveness

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

${effectiveness}

## Reproduction Log[*](reproducibility.md)

To add to this reproduction log, modify [this template](${template}) and run `bin/build.sh` to rebuild the documentation.