README.md

metadata

tags: autotrain
language: es
widget:
  - text: I love AutoTrain 🤗
datasets:
  - gabitoo1234/autotrain-data-mut_all_text
co2_eq_emissions: 115.48848403681228

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 680820343
• CO2 Emissions (in grams): 115.48848403681228

Validation Metrics

• Loss: 0.3041240870952606
• Accuracy: 0.9462770369425126
• Macro F1: 0.7836898686625933
• Micro F1: 0.9462770369425126
• Weighted F1: 0.9449148298990091
• Macro Precision: 0.8344505891491089
• Micro Precision: 0.9462770369425126
• Weighted Precision: 0.9451247372908952
• Macro Recall: 0.7568785255994025
• Micro Recall: 0.9462770369425126
• Weighted Recall: 0.9462770369425126

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/gabitoo1234/autotrain-mut_all_text-680820343

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("gabitoo1234/autotrain-mut_all_text-680820343", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("gabitoo1234/autotrain-mut_all_text-680820343", use_auth_token=True)

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

outputs = model(**inputs)