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文本分类 - 多个训练数据集

[英]Text Classification - Multiple Training Datasets

原文 2022-01-18 04:54:44 8 1 python/ text-classification

Would there be “dilution” of accuracy if I train the same text classification model with multiple training datasets?如果我用多个训练数据集训练相同的文本分类 model，准确性会“稀释”吗？ For example, my end users would be providing (uploading) their own tagged CSVs to train the model and use the trained model in the future.例如，我的最终用户将提供（上传）他们自己的标记 CSV 来训练 model 并在未来使用训练后的 model。 The contexts of datasets would be different - L&D, Technology, Customer Support, etc.数据集的上下文会有所不同——L&D、技术、客户支持等。

If yes, how do I have a “separate instance or model” for each user?如果是，我如何为每个用户创建一个“单独的实例或模型”？

I am using Python and would possibly use Gradio or Streamlit as the UI.我正在使用 Python 并且可能会使用 Gradio 或 Streamlit 作为 UI。 Open to advice.接受建议。

1 个解决方案

I ended up using huggingface's zero-shot classification.我最终使用了拥抱脸的零样本分类。

文本分类 CNN 过拟合训练 - Text classification CNN overfits training

使用多个数据集训练神经网络 (Keras) - Training a Neural Network with Multiple Datasets (Keras)

文本分类的训练和验证准确性和损失 - training and validation accuracy and loss for text classification

Keras 字符级 LSTM 文本分类未训练 - Keras character level LSTM text classification not training

训练一个基本的 spacy 文本分类模型 - Training a basic spacy text classification model

文本二元分类训练期间的波动损失 - Fluctuating loss during training for text binary classification

使用 spaCy 训练自定义文本分类 model - Training a custom text classification model using spaCy

为多个（分类）任务训练 wav2vec2 - Training wav2vec2 for multiple (classification) tasks

多个标签的文本分类 - Text Classification for multiple label

AttributeError：模块“torchtext.datasets”没有属性“text_classification” - AttributeError: module 'torchtext.datasets' has no attribute 'text_classification'

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相关问题 文本分类 CNN 过拟合训练 - Text classification CNN overfits training 使用多个数据集训练神经网络 (Keras) - Training a Neural Network with Multiple Datasets (Keras) 文本分类的训练和验证准确性和损失 - training and validation accuracy and loss for text classification Keras 字符级 LSTM 文本分类未训练 - Keras character level LSTM text classification not training 训练一个基本的 spacy 文本分类模型 - Training a basic spacy text classification model 文本二元分类训练期间的波动损失 - Fluctuating loss during training for text binary classification 使用 spaCy 训练自定义文本分类 model - Training a custom text classification model using spaCy 为多个（分类）任务训练 wav2vec2 - Training wav2vec2 for multiple (classification) tasks 多个标签的文本分类 - Text Classification for multiple label AttributeError：模块“torchtext.datasets”没有属性“text_classification” - AttributeError: module 'torchtext.datasets' has no attribute 'text_classification'

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