nlp_structbert_emotion-classification_chinese-tiny

iic/nlp_structbert_emotion-classification_chinese-tiny

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StructBERT中文情绪分类模型介绍情绪分类任务，通常为输入一段句子或一段话，识别该句话情绪类别的模型。在用户评价、观点抽取、意图识别中往往起到重要作用。模型基于Structbert-tiny-chinese，在情绪分类的数据集上fine-tune得到。模型可识别的情绪包含（恐惧、愤怒、厌恶、喜好、悲伤、高兴、惊讶）七种类别。

Text Processing

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Model details

模型介绍

中文整理

StructBERT中文情绪分类模型介绍

情绪分类任务，通常为输入一段句子或一段话，识别该句话情绪类别的模型。在用户评价、观点抽取、意图识别中往往起到重要作用。

模型描述

模型基于Structbert-tiny-chinese，在情绪分类的数据集上fine-tune得到。模型可识别的情绪包含（恐惧、愤怒、厌恶、喜好、悲伤、高兴、惊讶）七种类别。

期望模型使用方式以及适用范围

你可以使用StructBERT中文情绪分类模型，对通用领域的中文情绪分类任务进行推理。输入自然语言文本，模型会给出该文本的情绪分类标签以及相应的概率。

如何使用

在安装完成ModelScope之后即可使用

推理代码范例

模型局限性以及可能的偏差

模型训练数据有限，效果可能存在一定偏差。

训练数据介绍

使用数据集分布情况如下：

高兴悲伤厌恶喜好恐惧惊讶愤怒无明显情绪

------ ------- ------- ------ ---------- ------ ------ ------ -------

训练集 10610 13418 6909 8236 820 1664 5312 32071

验证集 1326 1677 863 1029 102 207 663 4008

数据评估及结果

该模型在验证集上的f1为0.4732。

数据评估及结果

优先采用原作者提供的中文模型卡片；仅有英文说明时由闲社AI翻译整理。重要参数、许可证和商用范围请以原文为准。

你将获得什么

完整仓库方式包含该固定版本中的权重、配置、分词器及说明文件；指定版本方式只下载所选文件或整组分片。多模态模型的投影文件、配置等依赖，请按作者说明配齐。

完整仓库可能包含多个权重格式，因此需要的磁盘空间可能大于单一格式的模型大小。下载文件不等于完成模型部署。

使用前须知

运行环境

运行模型需要的设备、工具与依赖，以原作者说明为准。

授权范围

是否允许商用、修改和分发，请查看模型许可证。

闲社提供资料与镜像下载方法，不代表已运行模型或完成安全审计。下载的代码应先检查，再执行。

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nlp_structbert_emotion-classification_chinese-tiny model download

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