readme: ---
  tags: autonlp
  language: unk
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - abhishek/autonlp-data-bbc-roberta
  co2_eq_emissions: 1.9859980179658823
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 37249301
  - CO2 Emissions (in grams): 1.9859980179658823
  
  ## Validation Metrics
  
  - Loss: 0.06406362354755402
  - Accuracy: 0.9833887043189369
  - Macro F1: 0.9832763664701248
  - Micro F1: 0.9833887043189369
  - Weighted F1: 0.9833288528828136
  - Macro Precision: 0.9847257743677181
  - Micro Precision: 0.9833887043189369
  - Weighted Precision: 0.9835392869652073
  - Macro Recall: 0.982101705176067
  - Micro Recall: 0.9833887043189369
  - Weighted Recall: 0.9833887043189369
  
  
  ## 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 AutoNLP"}' https://api-inference.huggingface.co/models/abhishek/autonlp-bbc-roberta-37249301
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("abhishek/autonlp-bbc-roberta-37249301", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("abhishek/autonlp-bbc-roberta-37249301", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```