readme: ---
  tags: autotrain
  language: en
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - crcb/autotrain-data-imp_hs
  co2_eq_emissions: 15.91710539314839
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 753423062
  - CO2 Emissions (in grams): 15.91710539314839
  
  ## Validation Metrics
  
  - Loss: 0.5205655694007874
  - Accuracy: 0.7746741154562383
  - Macro F1: 0.5796696218586866
  - Micro F1: 0.7746741154562382
  - Weighted F1: 0.7602379277947592
  - Macro Precision: 0.6976905233970596
  - Micro Precision: 0.7746741154562383
  - Weighted Precision: 0.7628815999440115
  - Macro Recall: 0.557144871405371
  - Micro Recall: 0.7746741154562383
  - Weighted Recall: 0.7746741154562383
  
  
  ## 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-imp_hs-753423062
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-imp_hs-753423062", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-imp_hs-753423062", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```