readme: ---
  language: unk
  datasets:
  - anwesham/autotrain-data-imdb-sentiment-analysis
  co2_eq_emissions: 0.2033402242358345
  ---
  
  - Problem type: Binary Classification
  - Model ID: 864927559
  - CO2 Emissions (in grams): 0.2033402242358345
  
  ## Validation Metrics
  
  - Loss: 0.18383920192718506
  - Accuracy: 0.9318
  - Precision: 0.9560625264047318
  - Recall: 0.9052
  - AUC: 0.98281574
  - F1: 0.9299363057324841
  
  ## 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 AutoTrain"}' https://api-inference.huggingface.co/models/anwesham/autotrain-imdb-sentiment-analysis-864927559
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("anwesham/autotrain-imdb-sentiment-analysis-864927559", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("anwesham/autotrain-imdb-sentiment-analysis-864927559", use_auth_token=True)
  
  inputs = tokenizer("I love to eat food", return_tensors="pt")
  
  outputs = model(**inputs)
  ```