Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 492513457
• CO2 Emissions (in grams): 5.527544460835904

Validation Metrics

• Loss: 0.07609463483095169
• Accuracy: 0.9735624586913417
• Macro F1: 0.9736173135739408
• Micro F1: 0.9735624586913417
• Weighted F1: 0.9736173135739408
• Macro Precision: 0.9737771415197378
• Micro Precision: 0.9735624586913417
• Weighted Precision: 0.9737771415197378
• Macro Recall: 0.9735624586913417
• Micro Recall: 0.9735624586913417
• Weighted Recall: 0.9735624586913417

Usage

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("wajidlinux99/gibberish-text-detector", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("wajidlinux99/gibberish-text-detector", use_auth_token=True)

inputs = tokenizer("Is this text really worth it?", return_tensors="pt")

outputs = model(**inputs)

Original Repository