readme: ---
  tags: autotrain
  language: unk
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - crcb/autotrain-data-carer_new
  co2_eq_emissions: 3.9861818439722594
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 781623992
  - CO2 Emissions (in grams): 3.9861818439722594
  
  ## Validation Metrics
  
  - Loss: 0.1639203429222107
  - Accuracy: 0.9389179755671903
  - Macro F1: 0.9055551236566716
  - Micro F1: 0.9389179755671903
  - Weighted F1: 0.9379300009988988
  - Macro Precision: 0.9466951148514304
  - Micro Precision: 0.9389179755671903
  - Weighted Precision: 0.9435523016000105
  - Macro Recall: 0.8818551804621082
  - Micro Recall: 0.9389179755671903
  - Weighted Recall: 0.9389179755671903
  
  
  ## 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 AutoTrain"}' https://api-inference.huggingface.co/models/crcb/autotrain-carer_new-781623992
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-carer_new-781623992", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-carer_new-781623992", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```