---
language: tr
license: mit
---
# turkish-text-classification-model

https://huggingface.co/algumusrende/turkish-text-classification-model

This model is used for Sentiment Analysis, which is based on bert-base-turkish-sentiment-cased https://huggingface.co/savasy/bert-base-turkish-sentiment-cased

## Dataset

The dataset is taken from https://www.kaggle.com/datasets/burhanbilenn/duygu-analizi-icin-urun-yorumlari?select=magaza_yorumlari_duygu_analizi.csv

Containing product reviews of electronics stores in Turkish Language, with 3 categories:

[
  "Olumlu (Positive)",
  "Olumsuz (Negative)", 
  "Tarafsız (Neutral)"
]

2 columns and 11429 rows (3 NaN rows), encoded in "utf-16"

*Dataset* 

| *size*   | *data* |
|--------|----|
|   5713 |train.csv|
|   2856 |val.csv|
|   2857 |test.tsv|
|  *11426* |*total*|

## Training and Results

|*index*|*eval\_loss*|*eval\_Accuracy*|*eval\_F1*|*eval\_Precision*|*eval\_Recall*|
|---|---|---|---|---|---|
|train|0\.41672539710998535|0\.8531419569403116|0\.8346503162224169|0\.842628684710363|0\.8315839726920476|
|val|0\.6787932515144348|0\.7545518207282913|0\.7277930570101517|0\.7311753495947505|0\.7293434379700242|
|test|0\.6885481476783752|0\.7434371718585929|0\.7170880702233838|0\.7189901255561661|0\.7180628887201386|

## Code Usage

```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

model = AutoModelForSequenceClassification.from_pretrained("algumusrende/turkish-text-classification-model")
tokenizer= AutoTokenizer.from_pretrained("algumusrende/turkish-text-classification-model")
pipe = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)

pipe("Son zamanlarda ekonomideki istikrar, borsa endeksine de olumlu yansıdı.")
# [{'label': 'Olumlu', 'score': 0.6654265522956848}]

pipe("Geçirdiğim diş operasyonu için çekilen röntgen filmleri sağlık yardımı kapsamında ödenmedi.")
# [{'label': 'Olumsuz', 'score': 0.9064584970474243}]

pipe("Eskiden bayramlarda çikolata dağıtlırdı, artık bunu göremiyoruz.")
# [{'label': 'Olumsuz', 'score': 0.7049197554588318}]

pipe("Ürün genel itibari ile iyi sayılır, ancak bazı eksikleri de var.")
# [{'label': 'Tarafsız', 'score': 0.9369649887084961}]

```
---