co2_eq_emissions: 0.021794705501614994 datasets:

• justpyschitry/autotrain-data-Psychiatry_Article_Identifier language: unk tags: "autotrain, psychiatry, ICD-11" widget:
• text: "I love AutoTrain 🤗"

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 990132820
• CO2 Emissions (in grams): 0.021794705501614994

Validation Metrics

• Loss: 0.3959168493747711
• Accuracy: 0.9141004862236629
• Macro F1: 0.8984327823035179
• Micro F1: 0.9141004862236629
• Weighted F1: 0.913962331636746
• Macro Precision: 0.9087151885944185
• Micro Precision: 0.9141004862236629
• Weighted Precision: 0.9154123644574501
• Macro Recall: 0.8957596627132517
• Micro Recall: 0.9141004862236629
• Weighted Recall: 0.9141004862236629

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/justpyschitry/autotrain-Psychiatry_Article_Identifier-990132820

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("justpyschitry/autotrain-Psychiatry_Article_Identifier-990132820", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("justpyschitry/autotrain-Psychiatry_Article_Identifier-990132820", use_auth_token=True)

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

outputs = model(**inputs)

Copyrights

(C) Justpsychiatry. CCBY 4.0 International. https://creativecommons.org/licenses/by/4.0/