readme: ---
  tags: autotrain
  language: tr
  widget:
  - text: "Bu ürün gerçekten güzel çıktı"
  datasets:
  - emre/autotrain-data-turkish-sentiment-analysis
  co2_eq_emissions: 120.82460124309924
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 870727732
  - CO2 Emissions (in grams): 120.82460124309924
  
  ## Validation Metrics
  
  - Loss: 0.1098366305232048
  - Accuracy: 0.9697853317600073
  - Macro F1: 0.9482820974460786
  - Micro F1: 0.9697853317600073
  - Weighted F1: 0.9695237873890088
  - Macro Precision: 0.9540948884759232
  - Micro Precision: 0.9697853317600073
  - Weighted Precision: 0.9694186941924757
  - Macro Recall: 0.9428467518468838
  - Micro Recall: 0.9697853317600073
  - Weighted Recall: 0.9697853317600073
  
  
  ## 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": "Bu ürün gerçekten güzel çıktı"}' https://api-inference.huggingface.co/models/emre/turkish-sentiment-analysis
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("emre/turkish-sentiment-analysis", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("emre/turkish-sentiment-analysis", use_auth_token=True)
  
  inputs = tokenizer("Bu ürün gerçekten güzel çıktı", return_tensors="pt")
  
  outputs = model(**inputs)
  ```