Tolga
Update README.md
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metadata
tags:
  - autotrain
  - text-classification
language:
  - tr
  - en
widget:
  - text: Aldığım hizmetten çok memnun kaldım... Yeniden göklerde görüşmek üzere...
datasets:
  - tkurtulus/thycomments
co2_eq_emissions:
  emissions: 1.2718440164245879
metrics:
  - accuracy
pipeline_tag: text-classification

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)