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turkish-text-classification-model
algumusrende/turkish-text-classification-model
turkish-text-classification-model is a text classification model from algumusrende. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
https://huggingface.co/algumusrende/turkish-text-classification-model
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- May 20, 2024
- Updated
- May 20, 2024
- SHA
- 639995f7
Model card
From the Hugging Face model README
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
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}]
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- tr
- Created
- May 20, 2024
- Updated
- May 20, 2024