metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - justpyschitry/autotrain-data-Wikipeida_Article_Classifier_by_Chap
co2_eq_emissions: 19.2150872382377

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 1022634731
CO2 Emissions (in grams): 19.2150872382377

Validation Metrics

Loss: 0.44044896960258484
Accuracy: 0.9149108589951378
Macro F1: 0.9112823337353622
Micro F1: 0.9149108589951378
Weighted F1: 0.9148129605580173
Macro Precision: 0.9142880779580832
Micro Precision: 0.9149108589951378
Weighted Precision: 0.9159535860210665
Macro Recall: 0.910063875934768
Micro Recall: 0.9149108589951378
Weighted Recall: 0.9149108589951378

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/justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634731

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634731", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("justpyschitry/autotrain-Wikipeida_Article_Classifier_by_Chap-1022634731", use_auth_token=True)

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

outputs = model(**inputs)