README.md

metadata

tags: autonlp
language: unk
widget:
  - text: I love AutoNLP 🤗
datasets:
  - abhishek/autonlp-data-swahili-sentiment
co2_eq_emissions: 1.9057858628956459

Model Trained Using AutoNLP

• Problem type: Multi-class Classification
• Model ID: 615517563
• CO2 Emissions (in grams): 1.9057858628956459

Validation Metrics

• Loss: 0.6990908980369568
• Accuracy: 0.695364238410596
• Macro F1: 0.6088819062581828
• Micro F1: 0.695364238410596
• Weighted F1: 0.677326207350606
• Macro Precision: 0.6945099492363175
• Micro Precision: 0.695364238410596
• Weighted Precision: 0.6938596845881614
• Macro Recall: 0.5738408020723632
• Micro Recall: 0.695364238410596
• Weighted Recall: 0.695364238410596

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/abhishek/autonlp-swahili-sentiment-615517563

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("abhishek/autonlp-swahili-sentiment-615517563", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("abhishek/autonlp-swahili-sentiment-615517563", use_auth_token=True)

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

outputs = model(**inputs)