numbda-webnews

Model Card for numbda-webnews

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numbda-webnews is a news classification model fine-tuned from roberta-base-finetuned-ifeng-chinese with a new dataset of approximately 40k news articles crawled from news websites in China.

The dataset contains (not limited to) the following 14 categories:

• 资讯
• 财经
• 体育
• 时政
• 娱乐
• 社会
• 科技
• 汽车
• 健康
• 萌宠
• 国际
• 生活
• 美食
• 游戏

The above 14 categories have a total of 26k samples.

Model Details

Model Sources [optional]

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• Repository: https://github.com/wenh06/numbda-webnews
• Huggingface Hub: https://huggingface.co/wenh06/numbda-webnews

Uses

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Direct Use

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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

# "wenh06/numbda-webnews" can be replaced with local path to the model directory
tokenizer = AutoTokenizer.from_pretrained("wenh06/numbda-webnews")
model = AutoModelForSequenceClassification.from_pretrained("wenh06/numbda-webnews")

pipeline = pipeline("text-classification", model=model, tokenizer=tokenizer)

Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

Training Details

Training Data

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This model was fine-tuned using a new dataset of approximately 40k news articles crawled from news websites in China, which would be released latter some time.

Evaluation

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Evaluation results and software/hardware information can be found in Weights & Biases.