# Model Card for `numbda-webnews`

<!-- Provide a quick summary of what the model is/does. -->

`numbda-webnews` is a news classification model fine-tuned from [roberta-base-finetuned-ifeng-chinese](https://huggingface.co/voidful/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]

<!-- Provide the basic links for the model. -->

- **Repository:** <https://github.com/wenh06/numbda-webnews>
- **Huggingface Hub:** <https://huggingface.co/wenh06/numbda-webnews>

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->

```python
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

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

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

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

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

<!-- This section describes the evaluation protocols and provides the results. -->

Evaluation results and software/hardware information can be found in [Weights & Biases](https://wandb.ai/wenh06/huggingface/runs/mg4uedxe/workspace?workspace=user-wenh06).

{"language": ["zh"], "license": "apache-2.0", "metrics": ["accuracy"], "pipeline_tag": "text-classification"}
transformers pytorch bert text-classification zh license:apache-2.0 autotrain_compatible endpoints_compatible region:us