README.md

metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - crcb/autotrain-data-imp_hs
co2_eq_emissions: 0.05286505617263864

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 753423076
• CO2 Emissions (in grams): 0.05286505617263864

Validation Metrics

• Loss: 0.539419412612915
• Accuracy: 0.7616387337057728
• Macro F1: 0.6428050387135232
• Micro F1: 0.761638733705773
• Weighted F1: 0.7592341595725172
• Macro Precision: 0.6606534010647378
• Micro Precision: 0.7616387337057728
• Weighted Precision: 0.7575825822976101
• Macro Recall: 0.6293404928847536
• Micro Recall: 0.7616387337057728
• Weighted Recall: 0.7616387337057728

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/crcb/autotrain-imp_hs-753423076

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("crcb/autotrain-imp_hs-753423076", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("crcb/autotrain-imp_hs-753423076", use_auth_token=True)

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

outputs = model(**inputs)