metadata
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: I love AutoTrain 🤗
datasets:
- tradero/autotrain-data-user-intent
co2_eq_emissions:
emissions: 0.46902644633558377
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 49241119078
- CO2 Emissions (in grams): 0.4690
Validation Metrics
- Loss: 1.676
- Accuracy: 0.800
- Macro F1: 0.733
- Micro F1: 0.800
- Weighted F1: 0.733
- Macro Precision: 0.700
- Micro Precision: 0.800
- Weighted Precision: 0.700
- Macro Recall: 0.800
- Micro Recall: 0.800
- Weighted Recall: 0.800
Usage
Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("tradero/distilbert-user-intent", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("tradero/distilbert-user-intent", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)