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autotrain-xlm-roberta-base-reviews-672119799

Text Classification
Transformers
PyTorch
Enawené-Nawé
xlm-roberta
Trained with AutoTrain
Inference Endpoints
Model card Files Community
autotrain-xlm-roberta-base-reviews-672119799 / README.md
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metadata
tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - YXHugging/autotrain-data-xlm-roberta-base-reviews
co2_eq_emissions: 1583.7188188958198

Model Trained Using AutoTrain

  • Problem type: Multi-class Classification
  • Model ID: 672119799
  • CO2 Emissions (in grams): 1583.7188188958198

Validation Metrics

  • Loss: 0.9590993523597717
  • Accuracy: 0.5827541666666667
  • Macro F1: 0.5806748283026683
  • Micro F1: 0.5827541666666667
  • Weighted F1: 0.5806748283026683
  • Macro Precision: 0.5834325027348383
  • Micro Precision: 0.5827541666666667
  • Weighted Precision: 0.5834325027348383
  • Macro Recall: 0.5827541666666667
  • Micro Recall: 0.5827541666666667
  • Weighted Recall: 0.5827541666666667

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/YXHugging/autotrain-xlm-roberta-base-reviews-672119799

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("YXHugging/autotrain-xlm-roberta-base-reviews-672119799", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("YXHugging/autotrain-xlm-roberta-base-reviews-672119799", use_auth_token=True)

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

outputs = model(**inputs)