Hugging Face's logo

Siddish
/
autotrain-yes-or-no-classifier-on-circa-1009033469

Text Classification
Transformers
PyTorch
English
roberta
Trained with AutoTrain
Inference Endpoints
Model card Files Community
1
autotrain-yes-or-no-classifier-on-circa-1009033469 / README.md
system's picture
system HF staff
Commit From AutoTrain
036376a
preview code
|
raw
history blame
1.47 kB
metadata
tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - Siddish/autotrain-data-yes-or-no-classifier-on-circa
co2_eq_emissions: 0.1287915253247826

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 1009033469
  • CO2 Emissions (in grams): 0.1287915253247826

Validation Metrics

  • Loss: 0.4084862470626831
  • Accuracy: 0.8722054859679721
  • Macro F1: 0.6340608446004876
  • Micro F1: 0.8722054859679722
  • Weighted F1: 0.8679846554644491
  • Macro Precision: 0.645023001823007
  • Micro Precision: 0.8722054859679721
  • Weighted Precision: 0.8656545967138464
  • Macro Recall: 0.6283763558287574
  • Micro Recall: 0.8722054859679721
  • Weighted Recall: 0.8722054859679721

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/Siddish/autotrain-yes-or-no-classifier-on-circa-1009033469

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Siddish/autotrain-yes-or-no-classifier-on-circa-1009033469", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Siddish/autotrain-yes-or-no-classifier-on-circa-1009033469", use_auth_token=True)

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

outputs = model(**inputs)