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vreese2414
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autotrain-test-frank-896929583

Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
Carbon Emissions
Inference Endpoints
Model card Files Community
autotrain-test-frank-896929583 / README.md
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metadata
tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - vreese2414/autotrain-data-test-frank
co2_eq_emissions: 20.85550802376653

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 896929583
  • CO2 Emissions (in grams): 20.85550802376653

Validation Metrics

  • Loss: 0.8998094797134399
  • Accuracy: 0.717983651226158
  • Macro F1: 0.6850466044284794
  • Micro F1: 0.717983651226158
  • Weighted F1: 0.7093970537930665
  • Macro Precision: 0.692166692035814
  • Micro Precision: 0.717983651226158
  • Weighted Precision: 0.7181745683190863
  • Macro Recall: 0.6985625924834511
  • Micro Recall: 0.717983651226158
  • Weighted Recall: 0.717983651226158

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/vreese2414/autotrain-test-frank-896929583

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("vreese2414/autotrain-test-frank-896929583", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("vreese2414/autotrain-test-frank-896929583", use_auth_token=True)

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

outputs = model(**inputs)