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---
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}]
```
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