readme: ---
  tags: autotrain
  language: unk
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - vlsb/autotrain-data-security-texts-classification-distilroberta
  co2_eq_emissions: 2.0817207656772445
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Binary Classification
  - Model ID: 688220764
  - CO2 Emissions (in grams): 2.0817207656772445
  
  ## Validation Metrics
  
  - Loss: 0.3055502772331238
  - Accuracy: 0.9030612244897959
  - Precision: 0.9528301886792453
  - Recall: 0.8782608695652174
  - AUC: 0.9439076757917337
  - F1: 0.9140271493212669
  
  ## 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/vlsb/autotrain-security-texts-classification-distilroberta-688220764
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("vlsb/autotrain-security-texts-classification-distilroberta-688220764", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```