readme: ---
  tags: autotrain
  language: unk
  widget:
  - text: "I love AutoTrain 🤗"
  datasets:
  - CH0KUN/autotrain-data-TNC_Data1000_wangchanBERTa
  co2_eq_emissions: 0.03882318406133382
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 927730545
  - CO2 Emissions (in grams): 0.03882318406133382
  
  ## Validation Metrics
  
  - Loss: 0.346664160490036
  - Accuracy: 0.9212962962962963
  - Macro F1: 0.9193830593356196
  - Micro F1: 0.9212962962962963
  - Weighted F1: 0.9213272351125573
  - Macro Precision: 0.920255423800781
  - Micro Precision: 0.9212962962962963
  - Weighted Precision: 0.9231182355921642
  - Macro Recall: 0.920208415963133
  - Micro Recall: 0.9212962962962963
  - Weighted Recall: 0.9212962962962963
  
  
  ## 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/CH0KUN/autotrain-TNC_Data1000_wangchanBERTa-927730545
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("CH0KUN/autotrain-TNC_Data1000_wangchanBERTa-927730545", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("CH0KUN/autotrain-TNC_Data1000_wangchanBERTa-927730545", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```