readme: ---
  tags: autonlp
  language: bn
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - albertvillanova/autonlp-data-indic_glue-multi_class_classification-1e67664
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 1311135
  
  ## Validation Metrics
  
  - Loss: 0.35616958141326904
  - Accuracy: 0.8979447200566973
  - Macro F1: 0.8545383956197669
  - Micro F1: 0.8979447200566975
  - Weighted F1: 0.8983951947775538
  - Macro Precision: 0.8615833774439791
  - Micro Precision: 0.8979447200566973
  - Weighted Precision: 0.9013559365881655
  - Macro Recall: 0.8516503001777104
  - Micro Recall: 0.8979447200566973
  - Weighted Recall: 0.8979447200566973
  
  
  ## 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/albertvillanova/autonlp-indic_glue-multi_class_classification-1e67664-1311135
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("albertvillanova/autonlp-indic_glue-multi_class_classification-1e67664-1311135", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("albertvillanova/autonlp-indic_glue-multi_class_classification-1e67664-1311135", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```