readme: ---
  tags: autonlp
  language: en
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - Someshfengde/autonlp-data-kaggledays
  co2_eq_emissions: 68.73074770596023
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 625717986
  - CO2 Emissions (in grams): 68.73074770596023
  
  ## Validation Metrics
  
  - Loss: 0.859463632106781
  - Accuracy: 0.6118427330852181
  - Macro F1: 0.6112554383858383
  - Micro F1: 0.6118427330852181
  - Weighted F1: 0.6112706859556324
  - Macro Precision: 0.6121119616189625
  - Micro Precision: 0.6118427330852181
  - Weighted Precision: 0.6121068719118146
  - Macro Recall: 0.6118067898609261
  - Micro Recall: 0.6118427330852181
  - Weighted Recall: 0.6118427330852181
  
  
  ## 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-625717986
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("Someshfengde/autonlp-kaggledays-625717986", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("Someshfengde/autonlp-kaggledays-625717986", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```