README.md

metadata

tags: autotrain
language: fr
widget:
  - text: I love AutoTrain 🤗
datasets:
  - ziedhajyahia/autotrain-data-ok
co2_eq_emissions: 5.096755166899446

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 848227025
• CO2 Emissions (in grams): 5.096755166899446

Validation Metrics

• Loss: 2.1917402744293213
• Accuracy: 0.44666666666666666
• Macro F1: 0.20291677804725128
• Micro F1: 0.44666666666666666
• Weighted F1: 0.37709801275435956
• Macro Precision: 0.19919016697588127
• Micro Precision: 0.44666666666666666
• Weighted Precision: 0.3478004329004329
• Macro Recall: 0.23167713239141807
• Micro Recall: 0.44666666666666666
• Weighted Recall: 0.44666666666666666

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/ziedhajyahia/autotrain-ok-848227025

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("ziedhajyahia/autotrain-ok-848227025", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("ziedhajyahia/autotrain-ok-848227025", use_auth_token=True)

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

outputs = model(**inputs)