Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 9705273
  • CO2 Emissions (in grams): 0.0006300767567816624

Validation Metrics

  • Loss: 0.15987505325856152
  • Accuracy: 0.9
  • Macro F1: 0.899749373433584
  • Micro F1: 0.9
  • Weighted F1: 0.8997493734335841
  • Macro Precision: 0.9023569023569024
  • Micro Precision: 0.9
  • Weighted Precision: 0.9023569023569025
  • Macro Recall: 0.9
  • Micro Recall: 0.9
  • Weighted Recall: 0.9

Usage

import json
import joblib
import pandas as pd

model = joblib.load('model.joblib')
config = json.load(open('config.json'))

features = config['features']

# data = pd.read_csv("data.csv")
data = data[features]
data.columns = ["feat_" + str(col) for col in data.columns]

predictions = model.predict(data)  # or model.predict_proba(data)
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Inference Examples
Inference API (serverless) does not yet support transformers models for this pipeline type.

Dataset used to train abhishek/autotrain-iris-logistic-regression