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charly
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autotrain-sentiment-4-812425472

Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
Inference Endpoints
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autotrain-sentiment-4-812425472 / README.md
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metadata
tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - charly/autotrain-data-sentiment-4
co2_eq_emissions: 0.007597570744740809

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 812425472
  • CO2 Emissions (in grams): 0.007597570744740809

Validation Metrics

  • Loss: 0.5105093121528625
  • Accuracy: 0.8268156424581006
  • Macro F1: 0.6020923520923521
  • Micro F1: 0.8268156424581006
  • Weighted F1: 0.8021395116367184
  • Macro Precision: 0.5907986111111111
  • Micro Precision: 0.8268156424581006
  • Weighted Precision: 0.7792248603351954
  • Macro Recall: 0.6141625496464206
  • Micro Recall: 0.8268156424581006
  • Weighted Recall: 0.8268156424581006

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/charly/autotrain-sentiment-4-812425472

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("charly/autotrain-sentiment-4-812425472", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("charly/autotrain-sentiment-4-812425472", use_auth_token=True)

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

outputs = model(**inputs)