README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - rajistics/autotrain-data-auditor-sentiment
co2_eq_emissions: 3.165771608457648

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 1167143226
• CO2 Emissions (in grams): 3.165771608457648

Validation Metrics

• Loss: 0.3418470025062561
• Accuracy: 0.8617131062951496
• Macro F1: 0.8448284352912685
• Micro F1: 0.8617131062951496
• Weighted F1: 0.8612696670395574
• Macro Precision: 0.8440532616584138
• Micro Precision: 0.8617131062951496
• Weighted Precision: 0.8612762332366959
• Macro Recall: 0.8461980005490884
• Micro Recall: 0.8617131062951496
• Weighted Recall: 0.8617131062951496

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/rajistics/autotrain-auditor-sentiment-1167143226

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("rajistics/autotrain-auditor-sentiment-1167143226", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("rajistics/autotrain-auditor-sentiment-1167143226", use_auth_token=True)

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

outputs = model(**inputs)