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TurkishAirlines-SentimentAnalysisModel
tolgadev/TurkishAirlines-SentimentAnalysisModel
TurkishAirlines-SentimentAnalysisModel is a text classification model from tolgadev. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 3023686751 - CO2 Emissions (in grams): 1.2718
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Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 3023686751
- CO2 Emissions (in grams): 1.2718
Validation Metrics
- Loss: 0.489
- Accuracy: 0.839
- Macro F1: 0.767
- Micro F1: 0.839
- Weighted F1: 0.832
- Macro Precision: 0.782
- Micro Precision: 0.839
- Weighted Precision: 0.845
- Macro Recall: 0.770
- Micro Recall: 0.839
- Weighted Recall: 0.839
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love to fly with Turkish Airlines"}' https://api-inference.huggingface.co/models/tkurtulus/TurkishAirlines-SentimentAnalysisModel
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("tkurtulus/TurkishAirlines-SentimentAnalysisModel")
tokenizer = AutoTokenizer.from_pretrained("tkurtulus/TurkishAirlines-SentimentAnalysisModel")
inputs = tokenizer("I love to fly with Turkish Airlines", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- convbert
- Languages
- tr, en
- Created
- Jan 23, 2023
- Updated
- Feb 9, 2024