readme: ---
  tags: autonlp
  language: en
  widget:
  - text: "I love AutoNLP 🤗"
  datasets:
  - ds198799/autonlp-data-predict_ROI_1
  co2_eq_emissions: 2.2439127664461718
  ---
  
  # Model Trained Using AutoNLP
  
  - Problem type: Multi-class Classification
  - Model ID: 29797730
  - CO2 Emissions (in grams): 2.2439127664461718
  
  ## Validation Metrics
  
  - Loss: 0.6314184069633484
  - Accuracy: 0.7596774193548387
  - Macro F1: 0.4740565300039588
  - Micro F1: 0.7596774193548386
  - Weighted F1: 0.7371623804622154
  - Macro Precision: 0.6747804619412134
  - Micro Precision: 0.7596774193548387
  - Weighted Precision: 0.7496542175358931
  - Macro Recall: 0.47743727441146655
  - Micro Recall: 0.7596774193548387
  - Weighted Recall: 0.7596774193548387
  
  
  ## 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/ds198799/autonlp-predict_ROI_1-29797730
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("ds198799/autonlp-predict_ROI_1-29797730", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("ds198799/autonlp-predict_ROI_1-29797730", use_auth_token=True)
  
  inputs = tokenizer("I love AutoNLP", return_tensors="pt")
  
  outputs = model(**inputs)
  ```