readme: ---
  tags: autonlp
  language: nl
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - maximedb/autonlp-data-vaccinchat
  co2_eq_emissions: 14.525955245648218
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 22134694
  - CO2 Emissions (in grams): 14.525955245648218
  
  ## Validation Metrics
  
  - Loss: 1.7039562463760376
  - Accuracy: 0.6369376479873717
  - Macro F1: 0.5363181342408181
  - Micro F1: 0.6369376479873717
  - Weighted F1: 0.6309793486221543
  - Macro Precision: 0.5533353910494714
  - Micro Precision: 0.6369376479873717
  - Weighted Precision: 0.676981050732216
  - Macro Recall: 0.5828723356986293
  - Micro Recall: 0.6369376479873717
  - Weighted Recall: 0.6369376479873717
  
  
  ## 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/maximedb/autonlp-vaccinchat-22134694
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("maximedb/autonlp-vaccinchat-22134694", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("maximedb/autonlp-vaccinchat-22134694", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```