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Crasher222
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kaggle-comp-test

Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
Inference Endpoints
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kaggle-comp-test / README.md
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metadata
tags: autonlp
language: en
widget:
  - text: I love AutoNLP 🤗
datasets:
  - Crasher222/autonlp-data-kaggle-test
co2_eq_emissions: 60.744727079482495

Model Trained Using AutoNLP

  • Problem type: Multi-class Classification
  • Model ID: 25805800
  • CO2 Emissions (in grams): 60.744727079482495

Validation Metrics

  • Loss: 0.4422711133956909
  • Accuracy: 0.8615328555811976
  • Macro F1: 0.8642434650461513
  • Micro F1: 0.8615328555811976
  • Weighted F1: 0.8617743626671308
  • Macro Precision: 0.8649112225076049
  • Micro Precision: 0.8615328555811976
  • Weighted Precision: 0.8625407179375096
  • Macro Recall: 0.8640777539828228
  • Micro Recall: 0.8615328555811976
  • Weighted Recall: 0.8615328555811976

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/Crasher222/autonlp-kaggle-test-25805800

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("Crasher222/autonlp-kaggle-test-25805800", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("Crasher222/autonlp-kaggle-test-25805800", use_auth_token=True)

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

outputs = model(**inputs)