README.md

metadata

tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - test1345/autonlp-data-savesome
co2_eq_emissions: 5.714250590300453

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 631818261
• CO2 Emissions (in grams): 5.714250590300453

Validation Metrics

• Loss: 0.44651690125465393
• Accuracy: 0.8792873051224944
• Macro F1: 0.839261602941426
• Micro F1: 0.8792873051224943
• Weighted F1: 0.8790427387522044
• Macro Precision: 0.8407634723656228
• Micro Precision: 0.8792873051224944
• Weighted Precision: 0.8801219917819031
• Macro Recall: 0.8400328140795883
• Micro Recall: 0.8792873051224944
• Weighted Recall: 0.8792873051224944

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 AutoNLP"}' https://api-inference.huggingface.co/models/test1345/autonlp-savesome-631818261

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("test1345/autonlp-savesome-631818261", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("test1345/autonlp-savesome-631818261", use_auth_token=True)

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

outputs = model(**inputs)