README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Yarn/autotrain-data-Traimn
co2_eq_emissions: 1.712176860015081

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 853827191
• CO2 Emissions (in grams): 1.712176860015081

Validation Metrics

• Loss: 0.10257730633020401
• Accuracy: 0.973421926910299
• Macro F1: 0.9735224586288418
• Micro F1: 0.973421926910299
• Weighted F1: 0.9735187934099364
• Macro Precision: 0.9738505933839127
• Micro Precision: 0.973421926910299
• Weighted Precision: 0.9738995774527256
• Macro Recall: 0.9734994306470444
• Micro Recall: 0.973421926910299
• Weighted Recall: 0.973421926910299

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/Yarn/autotrain-Traimn-853827191

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Yarn/autotrain-Traimn-853827191", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Yarn/autotrain-Traimn-853827191", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)