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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak quote

Justyna Jupowicz-Kozak

CEO of Professional Science Editing for Scientists @ prosciediting.com

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text for training

Grammar usage guide and real-world examples

USAGE SUMMARY

The phrase "text for training" is correct and usable in written English.
It can be used when referring to written material that is intended to be used for training purposes, such as in machine learning or educational contexts. Example: "We need to gather a diverse set of text for training our language model to improve its accuracy."

✓ Grammatically correct

Science

News & Media

Human-verified examples from authoritative sources

Exact Expressions

2 human-written examples

First of all, the training process initially takes 10 minutes to get started – but requires a lot more user input, learning and training to move anywhere beyond 80% accuracy (80% is the Microsoft claim – and somewhat ironically the Gates book 'The Road Ahead' is used as text for training).

News & Media

TechCrunch

Our findings indicate that full patents are considerably harder to analyze than patent abstracts and clearly confirm the common wisdom that using the same text genre (patent vs. scientific) and text type (abstract vs. full text) for training and testing is a pre-requisite for achieving high quality text mining results.

Human-verified similar examples from authoritative sources

Similar Expressions

58 human-written examples

Overall, our results emphasize the common wisdom that using the same text genre (patents vs. scientific articles) and text type (abstracts vs. full texts) for training and application is a pre-requisite for achieving high-quality text mining results.

Before presenting the Chemical Named Entity Recognition CNERR) approaches, Table 2 describes the available manually annotated text corpora for training and assessment of CNER tools according to the chemical entities focus, reference and source.

For the predictive functionality he says he used an open source random text generator for training character recurrent neural network intensifiers — adapted to "get the probabilities out, so that you can try to block things by probabilities," as he puts it.

News & Media

TechCrunch

PV introduces text embedding into word2vec for training distributed text representation.

A text corpus (CHEMDNER Corpusk) for training and evaluation purposes was annotated by a domain expert according to particular annotation rules for this task.

Two models (RNNLM-Freq/Brown) with 300 hidden units are trained on the entire training text for comparisons.

By extracting features such as unigrams (single words), bigrams (pairs of words) or trigrams (triples of words) from the tokenized text, this can be used for training the classifier and to classify new texts once the classifier has been trained.

Section 2 starts with a short overview about the source data used either for text classification, training acoustic and language models, and testing the Slovak LVCSR system.

The corpus we have annotated following the Variome Annotation Schema introduced in this article will serve as an important resource for training and evaluating text mining tools that target information extraction of genetic variation and its relationship to disease.

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Expert writing Tips

Best practice

When preparing machine learning models, ensure your "text for training" is diverse and representative of the data the model will encounter in real-world scenarios.

Common error

Avoid using a narrow or biased set of "text for training", as this can lead to models that perform poorly on unseen data. Always validate your model against a separate test set to ensure generalization.

Antonio Rotolo, PhD - Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Antonio Rotolo, PhD

Digital Humanist | Computational Linguist | CEO @Ludwig.guru

Source & Trust

84%

Authority and reliability

4.1/5

Expert rating

Real-world application tested

Linguistic Context

The phrase "text for training" primarily functions as a noun phrase. It identifies the type of written content that is used in a training process. As Ludwig AI tells us, "text for training" is correct and usable in written English.

Expression frequency: Uncommon

Frequent in

Science

60%

News & Media

30%

Formal & Business

10%

Less common in

Wiki

0%

Encyclopedias

0%

Reference

0%

Ludwig's WRAP-UP

In summary, the phrase "text for training" is grammatically correct and primarily serves to identify written content used in training contexts, particularly in science and technology. Ludwig AI confirms its usability in written English. While not exceedingly common, it is well-understood and correctly applied across diverse sources. Related phrases include "training text" and "training dataset", offering similar meanings. When using "text for training", ensure the material is diverse and representative to avoid bias. Overall, this phrase is a useful descriptor in educational and machine learning discussions.

FAQs

How can I use "text for training" in a sentence?

You can use "text for training" to refer to any written material used to educate or train a model or individual. For instance: "We need to gather a diverse set of "text for training" our language model."

What are some alternatives to "text for training"?

Alternatives include "training text", "training dataset", or "training material", depending on the context.

What makes a good "text for training" dataset?

A good "text for training" dataset should be comprehensive, representative of the task, and properly annotated if needed for supervised learning.

Which type of "text for training" is best for NLP models?

The ideal "text for training" for Natural Language Processing (NLP) models varies depending on the task. For example, training a sentiment analysis model requires text with sentiment labels, while a language model benefits from a broad range of unlabeled text.

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Source & Trust

84%

Authority and reliability

4.1/5

Expert rating

Real-world application tested

Most frequent sentences: