autotrain-TNC_Data1000_wangchanBERTa-927730545 – AI Model by CH0KUN | AlphaNeural AI

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CH0KUN/
autotrain-TNC_Data1000_wangchanBERTa-927730545

like

0

text-classification

CH0KUN/autotrain-data-TNC_Data1000_wangchanBERTa

co2_eq_emissions

autotrain_compatible

endpoints_compatible

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Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 927730545
CO2 Emissions (in grams): 0.03882318406133382

Validation Metrics

Loss: 0.346664160490036
Accuracy: 0.9212962962962963
Macro F1: 0.9193830593356196
Micro F1: 0.9212962962962963
Weighted F1: 0.9213272351125573
Macro Precision: 0.920255423800781
Micro Precision: 0.9212962962962963
Weighted Precision: 0.9231182355921642
Macro Recall: 0.920208415963133
Micro Recall: 0.9212962962962963
Weighted Recall: 0.9212962962962963

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/CH0KUN/autotrain-TNC_Data1000_wangchanBERTa-927730545

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("CH0KUN/autotrain-TNC_Data1000_wangchanBERTa-927730545", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("CH0KUN/autotrain-TNC_Data1000_wangchanBERTa-927730545", use_auth_token=True)

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

outputs = model(**inputs)