readme: ---
  tags: autonlp
  language: en
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - Someshfengde/autonlp-data-kaggledays
  co2_eq_emissions: 28.622267513847273
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 625717992
  - CO2 Emissions (in grams): 28.622267513847273
  
  ## Validation Metrics
  
  - Loss: 0.8782362937927246
  - Accuracy: 0.6022282660559214
  - Macro F1: 0.6024258279848015
  - Micro F1: 0.6022282660559214
  - Weighted F1: 0.6024299908624371
  - Macro Precision: 0.604093172183357
  - Micro Precision: 0.6022282660559214
  - Weighted Precision: 0.6041166306778806
  - Macro Recall: 0.6022424576798522
  - Micro Recall: 0.6022282660559214
  - Weighted Recall: 0.6022282660559214
  
  
  ## 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/Someshfengde/autonlp-kaggledays-625717992
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("Someshfengde/autonlp-kaggledays-625717992", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("Someshfengde/autonlp-kaggledays-625717992", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```