NemoCurator Quality Classifier DeBERTa

Model Overview

This is a text classification model that can enable qualitative data annotation, creation of quality-specific blends and addition of metadata tags. The model classifies documents into one of three classes based on the quality of the document: \"High\", \"Medium\", \"Low\"

The model was trained using data annotated by human annotators, who considered quality factors such as content accuracy, clarity, coherence, grammar, depth of information, and overall usefulness of the document.

This model is used in the NVIDIA NeMo Curator as part of the qualitative filtering module.

Model Architecture

The model architecture is Deberta V3 Base\nContext length is 1024 tokens

Training (details)

Training data:

The training set is 22828 Common Crawl text samples, labeled as \"High\", \"Medium\", \"Low\". Here are some examples:

Input:

Volunteering\n\nIt's all about the warm, fuzzy feeling when you serve the community, without expectation of gain. Volunteering offers you the necessary experience and development skills to take forward with you, as you venture out to work with other people and apply what you learn, to achieve your career goals.\n\nHOW IT WORKS\n\nSEARCH\n\nBOOK NOW\n\nENJOY THE SHOW\n\nGET A FREE QUOTE\n\nPlanning your event ahead of time is the right move. Contact our experts and let us surprise you.\n

Output: Low

Input:

Sharapova has been in New Zealand since well before the New Year, preparing for her 2011 start and requested the opening day match to test her form. \"My last tournament was over two months ago and it will be really good to get back playing again.\"\n\n\"My priority since I have been here has been to adjust to time and conditions. I have had a couple of practices a day and think that has been really important.\"\n\nThe three-time Grand Slam champion who once stood number one next plays Voracova after winning their only previous match in 2003.\n

Output: High

How To Use This Model

Input

The model takes one or several paragraphs of text as input.

Example input:

Reasons to visit Thatta\n\nThatta is one of the most important cities of the province of Sindh, Pakistan. Historically it is the richest city. The sands of Thatta have seen many great men. It provided Alexander the Great and his troops a comfortable resting place before they moved further. It welcomed the Mughal Emperor Shah Jehan.\n

Output

The model outputs one of the 3 classes as the predicted quality for each input sample.

Example output:

Medium\n

How to use in NeMo Curator

The inference code is available on NeMo Curator's GitHub repository. Download the model.pth and check out this example notebook to get started.

Evaluation Benchmarks

Evaluation data

The evaluation data is a subset of training data where all three annotators agree on the label. It has 7128 samples.

Results

Accuracy score on evaluation set with 7128 samples - 0.8252

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

	Precision	Recall	F1-Score
High	0.5043	0.1776	0.2626
Medium	0.8325	0.9396	0.8825
Low	0.8510	0.7279	0.7842

Confusion Matrix:

We verify that the predicted scores are indeed close to their ground truth, and are due to the noisy nature of the annotation.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

	High	Medium	Low
High	117	541	1
Medium	115	4688	187
Low	0	402	1077

Limitations

Subjectivity in Quality: Quality assessment is inherently subjective and may vary among different annotators.

References

License

License to use this model is covered by the Apache 2.0. By downloading the public and release version of the model, you accept the terms and conditions of the Apache License 2.0.\nThis repository contains the code for the domain classifier model.

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The model classifies documents into one of three classes based on the quality of the document: \"High\", \"Medium\", \"Low\"\n\nThe model was trained using data annotated by human annotators, who considered quality factors such as content accuracy, clarity, coherence, grammar, depth of information, and overall usefulness of the document.\n\nThis model is used in the [NVIDIA NeMo Curator](https://github.com/NVIDIA/NeMo-Curator) as part of the qualitative filtering module.\n\n## Model Architecture\n\nThe model architecture is Deberta V3 Base\nContext length is 1024 tokens\n\n## Training (details)\n\n### Training data:\n\nThe training set is 22828 Common Crawl text samples, labeled as \"High\", \"Medium\", \"Low\". Here are some examples:\n1. Input:\n\n ```\n Volunteering\n\n It's all about the warm, fuzzy feeling when you serve the community, without expectation of gain. Volunteering offers you the necessary experience and development skills to take forward with you, as you venture out to work with other people and apply what you learn, to achieve your career goals.\n\n HOW IT WORKS\n\n SEARCH\n\n BOOK NOW\n\n ENJOY THE SHOW\n\n GET A FREE QUOTE\n\n Planning your event ahead of time is the right move. Contact our experts and let us surprise you.\n ```\n\n Output: `Low`\n\n2. Input:\n\n ```\n Sharapova has been in New Zealand since well before the New Year, preparing for her 2011 start and requested the opening day match to test her form. \"My last tournament was over two months ago and it will be really good to get back playing again.\"\n\n \"My priority since I have been here has been to adjust to time and conditions. I have had a couple of practices a day and think that has been really important.\"\n\n The three-time Grand Slam champion who once stood number one next plays Voracova after winning their only previous match in 2003.\n ```\n\n Output: `High`\n\n## How To Use This Model\n\n### Input\n\nThe model takes one or several paragraphs of text as input.\n\nExample input:\n\n```\nReasons to visit Thatta\n\nThatta is one of the most important cities of the province of Sindh, Pakistan. Historically it is the richest city. The sands of Thatta have seen many great men. It provided Alexander the Great and his troops a comfortable resting place before they moved further. It welcomed the Mughal Emperor Shah Jehan.\n```\n\n### Output\n\nThe model outputs one of the 3 classes as the predicted quality for each input sample.\n\nExample output:\n\n```\nMedium\n```\n\n## How to use in NeMo Curator\n\nThe inference code is available on [NeMo Curator's GitHub repository](https://github.com/NVIDIA/NeMo-Curator). Download the [model.pth](https://huggingface.co/nvidia/quality-classifier-deberta/blob/main/model.pth) and check out this [example notebook](https://github.com/NVIDIA/NeMo-Curator/blob/main/tutorials/distributed_data_classification/distributed_data_classification.ipynb) to get started.\n\n\n## Evaluation Benchmarks\n\n### Evaluation data\n\nThe evaluation data is a subset of training data where all three annotators agree on the label. It has 7128 samples.\n\n### Results\n\nAccuracy score on evaluation set with 7128 samples - `0.8252`\n\n| | Precision | Recall | F1-Score |\n|--------|-----------|--------|----------|\n| High | 0.5043 | 0.1776 | 0.2626 |\n| Medium | 0.8325 | 0.9396 | 0.8825 |\n| Low | 0.8510 | 0.7279 | 0.7842 |\n\nConfusion Matrix:\n\nWe verify that the predicted scores are indeed close to their ground truth, and are due to the noisy nature of the annotation.\n\n| | High | Medium | Low |\n|---------|------|--------|-----|\n| High | 117 | 541 | 1 |\n| Medium | 115 | 4688 | 187 |\n| Low | 0 | 402 | 1077|\n\n## Limitations\n\n- Subjectivity in Quality: Quality assessment is inherently subjective and may vary among different annotators.\n\n## References\n\n- https://arxiv.org/abs/2111.09543\n- https://github.com/microsoft/DeBERTa\n\n## License\n\nLicense to use this model is covered by the Apache 2.0. 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