readme: ---
  tags: autotrain
  language: ja
  widget:
  - text: "Windows 11搭載PCを買ったら最低限やっておきたいこと"
  - text: "3月デスクトップOSシェア、Windowsが増加しMacが減少"
  - text: "raytrek、Core i7-12700HとRTX 3070 Tiを搭載するノートPC"
  datasets:
  - jicoc22578/autotrain-data-livedoor_news
  co2_eq_emissions: 0.019299491458156143
  ---
  
  # Model Trained Using AutoTrain
  
  - Problem type: Multi-class Classification
  - Model ID: 722922024
  - CO2 Emissions (in grams): 0.019299491458156143
  
  ## Validation Metrics
  
  - Loss: 0.19609540700912476
  - Accuracy: 0.9457627118644067
  - Macro F1: 0.9404319054946133
  - Micro F1: 0.9457627118644067
  - Weighted F1: 0.9456037443251943
  - Macro Precision: 0.9420917371721244
  - Micro Precision: 0.9457627118644067
  - Weighted Precision: 0.9457910238180336
  - Macro Recall: 0.9391783746329772
  - Micro Recall: 0.9457627118644067
  - Weighted Recall: 0.9457627118644067
  
  
  ## 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/jicoc22578/autotrain-livedoor_news-722922024
  ```
  
  Or Python API:
  
  ```
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model = AutoModelForSequenceClassification.from_pretrained("jicoc22578/autotrain-livedoor_news-722922024", use_auth_token=True)
  
  tokenizer = AutoTokenizer.from_pretrained("jicoc22578/autotrain-livedoor_news-722922024", use_auth_token=True)
  
  inputs = tokenizer("I love AutoTrain", return_tensors="pt")
  
  outputs = model(**inputs)
  ```