autotrain-kaggle-effective-arguments-1086739296 – AI Model by Danitg95 | AlphaNeural AI

You can deploy this model and start earning money today!

Danitg95/
autotrain-kaggle-effective-arguments-1086739296

like

0

text-classification

Danitg95/autotrain-data-kaggle-effective-arguments

co2_eq_emissions

autotrain_compatible

endpoints_compatible

Views

No views yet

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 1086739296
CO2 Emissions (in grams): 5.2497206864306065

Validation Metrics

Loss: 0.744236171245575
Accuracy: 0.6719238613188308
Macro F1: 0.5450301061253738
Micro F1: 0.6719238613188308
Weighted F1: 0.6349879540623229
Macro Precision: 0.6691326843926052
Micro Precision: 0.6719238613188308
Weighted Precision: 0.6706209016443158
Macro Recall: 0.5426627824078865
Micro Recall: 0.6719238613188308
Weighted Recall: 0.6719238613188308

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/Danitg95/autotrain-kaggle-effective-arguments-1086739296

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Danitg95/autotrain-kaggle-effective-arguments-1086739296", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Danitg95/autotrain-kaggle-effective-arguments-1086739296", use_auth_token=True)

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

outputs = model(**inputs)