README.md

metadata

tags: autotrain
language: en
widget:
  - text: I love AutoTrain 🤗
datasets:
  - snap/autotrain-data-argument-feedback
co2_eq_emissions: 39.98165454365982

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 1154042510
• CO2 Emissions (in grams): 39.98165454365982

Validation Metrics

• Loss: 0.7440880537033081
• Accuracy: 0.6724677090414684
• Macro F1: 0.5448715054903115
• Micro F1: 0.6724677090414684
• Weighted F1: 0.6355527198056449
• Macro Precision: 0.658141341119219
• Micro Precision: 0.6724677090414684
• Weighted Precision: 0.6654291773298342
• Macro Recall: 0.5406790407797492
• Micro Recall: 0.6724677090414684
• Weighted Recall: 0.6724677090414684

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/snap/autotrain-argument-feedback-1154042510

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("snap/autotrain-argument-feedback-1154042510", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("snap/autotrain-argument-feedback-1154042510", use_auth_token=True)

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

outputs = model(**inputs)