metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - rabiaqayyum/autotrain-data-mental-health-analysis
co2_eq_emissions: 313.3534743349287

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 752423172
CO2 Emissions (in grams): 313.3534743349287

Validation Metrics

Loss: 0.6064515113830566
Accuracy: 0.805171240644137
Macro F1: 0.7253473044054398
Micro F1: 0.805171240644137
Weighted F1: 0.7970679970423672
Macro Precision: 0.7477679873153633
Micro Precision: 0.805171240644137
Weighted Precision: 0.7966263131173029
Macro Recall: 0.7143231260991618
Micro Recall: 0.805171240644137
Weighted Recall: 0.805171240644137

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/rabiaqayyum/autotrain-mental-health-analysis-752423172

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("rabiaqayyum/autotrain-mental-health-analysis-752423172", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("rabiaqayyum/autotrain-mental-health-analysis-752423172", use_auth_token=True)

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

outputs = model(**inputs)