AutoTrain-LUC-COMP429-VEAA-Classification – AI Model by NicholasSynovic | AlphaNeural AI

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NicholasSynovic/
AutoTrain-LUC-COMP429-VEAA-Classification

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text-classification

NicholasSynovic/autotrain-data-luc-comp429-victorian-authorship-classification

co2_eq_emissions

autotrain_compatible

endpoints_compatible

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Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 52472123757
CO2 Emissions (in grams): 4.1360

This model reuses and extends a Bert model trained on NicholasSynovic/Free-AutoTrain-VEAA

Validation Metrics

Loss: 1.425
Accuracy: 0.636
Macro F1: 0.504
Micro F1: 0.636
Weighted F1: 0.624
Macro Precision: 0.523
Micro Precision: 0.636
Weighted Precision: 0.630
Macro Recall: 0.508
Micro Recall: 0.636
Weighted Recall: 0.636

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/NicholasSynovic/autotrain-luc-comp429-victorian-authorship-classification-52472123757

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("NicholasSynovic/AutoTrain-LUC-COMP429-VEAA-Classification", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("NicholasSynovic/autotrain-luc-comp429-victorian-authorship-classification-52472123757", use_auth_token=True)

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

outputs = model(**inputs)