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---
language: tr
Dataset: interpress_news_category_tr
---
# INTERPRESS NEWS CLASSIFICATION
## Dataset
The dataset downloaded from interpress. This dataset is real world data. Actually there are 273K data but I filtered them and used 108K data for this model. For more information about dataset please visit this [link](https://huggingface.co/datasets/interpress_news_category_tr_lite)
## Model
Model accuracy on train data and validation data is %97.
## Usage
```sh
pip install transformers or pip install transformers==4.3.3
```
```sh
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("serdarakyol/interpress-turkish-news-classification")
model = AutoModelForSequenceClassification.from_pretrained("serdarakyol/interpress-turkish-news-classification")
```
```sh
import torch
import numpy as np
if torch.cuda.is_available():
device = torch.device("cuda")
model = model.cuda()
print('There are %d GPU(s) available.' % torch.cuda.device_count())
print('GPU name is:', torch.cuda.get_device_name(0))
else:
print('No GPU available, using the CPU instead.')
device = torch.device("cpu")
```
```sh
def prediction(news):
news=[news]
indices=tokenizer.batch_encode_plus(
news,
max_length=512,
add_special_tokens=True,
return_attention_mask=True,
padding='max_length',
truncation=True,
return_tensors='pt') # for tf tensors, switch pt to tf
inputs = indices["input_ids"].clone().detach().to(device)
masks = indices["attention_mask"].clone().detach().to(device)
with torch.no_grad():
output = model(inputs, token_type_ids=None,attention_mask=masks)
logits = output[0]
logits = logits.detach().cpu().numpy()
pred = np.argmax(logits,axis=1)[0]
return pred
```
```sh
news = r"ABD'den Prens Selman'a yaptırım yok Beyaz Saray Sözcüsü Psaki, Muhammed bin Selman'a yaptırım uygulamamanın \"doğru karar\" olduğunu savundu. Psaki, \"Tarihimizde, Demokrat ve Cumhuriyetçi başkanların yönetimlerinde diplomatik ilişki içinde olduğumuz ülkelerin liderlerine yönelik yaptırım getirilmemiştir\" dedi."
```
You can find the news in this [link](https://www.ntv.com.tr/dunya/abdden-prens-selmana-yaptirim-yok,YTeWNv0-oU6Glbhnpjs1JQ)
news data: 02/03/2021
```sh
labels = {
0 : "Culture-Art",
1 : "Economy",
2 : "Politics",
3 : "Education",
4 : "World",
5 : "Sport",
6 : "Technology",
7 : "Magazine",
8 : "Health",
9 : "Agenda"
}
pred = prediction(news)
print(labels[pred])
# > World
```
Thanks to @yavuzkomecoglu for contributes
If you have any question, please, don't hesitate to contact with me
[](https://www.linkedin.com/in/serdarakyol55/)
[](https://github.com/serdarakyol) |