README.md

metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - erixxdp/autotrain-data-gsemodel
co2_eq_emissions: 0.027846282970913613

Model Trained Using AutoTrain

• Problem type: Multi-class Classification
• Model ID: 1148842296
• CO2 Emissions (in grams): 0.027846282970913613

Validation Metrics

• Loss: 0.4816772937774658
• Accuracy: 0.864
• Macro F1: 0.865050349743783
• Micro F1: 0.864
• Weighted F1: 0.865050349743783
• Macro Precision: 0.8706266090178479
• Micro Precision: 0.864
• Weighted Precision: 0.8706266090178482
• Macro Recall: 0.864
• Micro Recall: 0.864
• Weighted Recall: 0.864

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/erixxdp/autotrain-gsemodel-1148842296

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("erixxdp/autotrain-gsemodel-1148842296", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("erixxdp/autotrain-gsemodel-1148842296", use_auth_token=True)

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

outputs = model(**inputs)