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autonlp-txc-17923124

Text Classification
Transformers
PyTorch
English
roberta
Trained with AutoTrain
Carbon Emissions
Inference Endpoints
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autonlp-txc-17923124 / README.md
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metadata
tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - emekaboris/autonlp-data-txc
co2_eq_emissions: 133.57087522185148

Model Trained Using AutoNLP

  • Problem type: Multi-class Classification
  • Model ID: 17923124
  • CO2 Emissions (in grams): 133.57087522185148

Validation Metrics

  • Loss: 0.2080804407596588
  • Accuracy: 0.9325402190077058
  • Macro F1: 0.7283811287183823
  • Micro F1: 0.9325402190077058
  • Weighted F1: 0.9315711955594153
  • Macro Precision: 0.8106599661500661
  • Micro Precision: 0.9325402190077058
  • Weighted Precision: 0.9324644116921059
  • Macro Recall: 0.7020515544343829
  • Micro Recall: 0.9325402190077058
  • Weighted Recall: 0.9325402190077058

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 AutoNLP"}' https://api-inference.huggingface.co/models/emekaboris/autonlp-txc-17923124

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("emekaboris/autonlp-txc-17923124", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("emekaboris/autonlp-txc-17923124", use_auth_token=True)

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

outputs = model(**inputs)