README.md

metadata

tags:
  - autotrain
  - text-classification
  - cognitive distortions
  - psychology
  - depression
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - halilbabacan/autotrain-data-cognitive_distortions
co2_eq_emissions:
  emissions: 0.8368333755010434

The article is under publication. For communication, you can send an e-mail to [email protected].

Model Trained Using AutoTrain

• Problem type: Binary Classification
• Model ID: 73482139269
• CO2 Emissions (in grams): 0.8368

Validation Metrics

• Loss: 0.076
• Accuracy: 0.973
• Precision: 0.912
• Recall: 0.995
• AUC: 0.997
• F1: 0.951

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/halilbabacan/autotrain-cognitive_distortions-73482139269

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("halilbabacan/autotrain-cognitive_distortions-73482139269", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("halilbabacan/autotrain-cognitive_distortions-73482139269", use_auth_token=True)

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

outputs = model(**inputs)