metadata

tags: autotrain
language: unk
widget:
  - text: I love AutoTrain 🤗
datasets:
  - EXOP/autotrain-data-exop-msc-flat-categories-multilingual
co2_eq_emissions: 652.3729662301374

Model Trained Using AutoTrain

Problem type: Multi-class Classification
Model ID: 1147942216
CO2 Emissions (in grams): 652.3729662301374

Validation Metrics

Loss: 0.4508252441883087
Accuracy: 0.8882102517882141
Macro F1: 0.7681095738330185
Micro F1: 0.8882102517882141
Weighted F1: 0.8873062298114072
Macro Precision: 0.8125021386404774
Micro Precision: 0.8882102517882141
Weighted Precision: 0.8875709606885154
Macro Recall: 0.7429489567097202
Micro Recall: 0.8882102517882141
Weighted Recall: 0.8882102517882141

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/EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216", use_auth_token=True)

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

outputs = model(**inputs)