readme: ---
  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)
  ```