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Commit From AutoTrain
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metadata
tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - sasha/autotrain-data-DistilBERT-TweetEval
co2_eq_emissions:
  emissions: 7.4450095136306444

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 1281148991
  • CO2 Emissions (in grams): 7.4450

Validation Metrics

  • Loss: 0.610
  • Accuracy: 0.739
  • Macro F1: 0.721
  • Micro F1: 0.739
  • Weighted F1: 0.739
  • Macro Precision: 0.727
  • Micro Precision: 0.739
  • Weighted Precision: 0.740
  • Macro Recall: 0.715
  • Micro Recall: 0.739
  • Weighted Recall: 0.739

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/sasha/autotrain-DistilBERT-TweetEval-1281148991

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("sasha/autotrain-DistilBERT-TweetEval-1281148991", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("sasha/autotrain-DistilBERT-TweetEval-1281148991", use_auth_token=True)

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

outputs = model(**inputs)