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Fix typos in poseval metric #738

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Fix typos in poseval metric #738

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4 changes: 2 additions & 2 deletions metrics/poseval/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@ tags:
- metric
description: >-
The poseval metric can be used to evaluate POS taggers. Since seqeval does not work well with POS data
that is not in IOB format the poseval is an alternative. It treats each token in the dataset as independant
that is not in IOB format the poseval is an alternative. It treats each token in the dataset as independent
observation and computes the precision, recall and F1-score irrespective of sentences. It uses scikit-learns's
classification report to compute the scores.
---
Expand All @@ -21,7 +21,7 @@ description: >-

## Metric description

The poseval metric can be used to evaluate POS taggers. Since seqeval does not work well with POS data (see e.g. [here](https://stackoverflow.com/questions/71327693/how-to-disable-seqeval-label-formatting-for-pos-tagging)) that is not in IOB format the poseval is an alternative. It treats each token in the dataset as independant observation and computes the precision, recall and F1-score irrespective of sentences. It uses scikit-learns's [classification report](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html) to compute the scores.
The poseval metric can be used to evaluate POS taggers. Since seqeval does not work well with POS data (see e.g. [here](https://stackoverflow.com/questions/71327693/how-to-disable-seqeval-label-formatting-for-pos-tagging)) that is not in IOB format the poseval is an alternative. It treats each token in the dataset as independent observation and computes the precision, recall and F1-score irrespective of sentences. It uses scikit-learns's [classification report](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html) to compute the scores.


## How to use
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2 changes: 1 addition & 1 deletion metrics/poseval/poseval.py
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Expand Up @@ -38,7 +38,7 @@
_DESCRIPTION = """\
The poseval metric can be used to evaluate POS taggers. Since seqeval does not work well with POS data \
(see e.g. [here](https://stackoverflow.com/questions/71327693/how-to-disable-seqeval-label-formatting-for-pos-tagging))\
that is not in IOB format the poseval metric is an alternative. It treats each token in the dataset as independant \
that is not in IOB format the poseval metric is an alternative. It treats each token in the dataset as independent \
observation and computes the precision, recall and F1-score irrespective of sentences. It uses scikit-learns's \
[classification report](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html) \
to compute the scores.
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