Modelpublic

palakagl/bert_MultiClass_TextClassification

sourceHugging Faceupdated 5y agoView on Hugging Face

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Model Card

Model Trained Using AutoTrain

—Problem type: Multi-class Classification
—Model ID: 717221775
—CO2 Emissions (in grams): 5.080390550458655

Validation Metrics

—Loss: 0.35279911756515503
—Accuracy: 0.9269102990033222
—Macro F1: 0.9261839948926327
—Micro F1: 0.9269102990033222
—Weighted F1: 0.9263981751760975
—Macro Precision: 0.9273912049203341
—Micro Precision: 0.9269102990033222
—Weighted Precision: 0.9280084437800646
—Macro Recall: 0.927250645380574
—Micro Recall: 0.9269102990033222
—Weighted Recall: 0.9269102990033222

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/palakagl/autotrain-PersonalAssitant-717221775

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("palakagl/autotrain-PersonalAssitant-717221775", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("palakagl/autotrain-PersonalAssitant-717221775", use_auth_token=True)

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

outputs = model(**inputs)