README.md

metadata

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)