README.md

metadata

tags:
  - autotrain
  - text-classification
language:
  - unk
widget:
  - text: I love AutoTrain
datasets:
  - trung0209/autotrain-data-rumi-bert-large-case
co2_eq_emissions:
  emissions: 0.8802978764048797

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 73218139171
• CO2 Emissions (in grams): 0.8803

Validation Metrics

• Loss: 0.285
• Accuracy: 0.938
• Macro F1: 0.935
• Micro F1: 0.938
• Weighted F1: 0.938
• Macro Precision: 0.947
• Micro Precision: 0.938
• Weighted Precision: 0.941
• Macro Recall: 0.929
• Micro Recall: 0.938
• Weighted Recall: 0.938

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/trung0209/autotrain-rumi-bert-large-case-73218139171

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("trung0209/autotrain-rumi-bert-large-case-73218139171", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("trung0209/autotrain-rumi-bert-large-case-73218139171", use_auth_token=True)

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

outputs = model(**inputs)