Model Card for Model ID

Turkish news classifier.

Model Description

11 classes are present: 'turkiye': 0, 'ekonomi': 1, 'dunya': 2, 'spor': 3, 'magazin': 4, 'guncel': 5, 'genel': 6, 'siyaset': 7, 'saglik': 8, 'kultur-sanat': 9, 'teknoloji': 10, 'yasam': 11

The model is a finetuned bert-base-multilingual-uncased model. The model is not originally a classifier model, so classifier weights were trained completely using the turkish dataset. 🤗

Eval loss: train_loss': 0.8327703781731708 Train loss:0.8896290063858032 Eval train split: 0.2/0.8

Developed by: [Ezel Bayraktar]
Model type: [Classifier]
Language(s) (NLP): [Turkish]
License: [MIT License]
Finetuned from model [optional]: [bert-base-multilingual-uncased]

Training Details

I used rtx 3060 12gb card to tain the training took 245 minutes in total

learning_rate=5e-5, per_device_train_batch_size=20, per_device_eval_batch_size=20, num_train_epochs=7,

Training Data

I used the kemik 42bin haber data set which you can access from this link http://www.kemik.yildiz.edu.tr/veri_kumelerimiz.html

Model Card Contact

[email protected]