Dacon Series
Collection
Dacon contest only used • 4 items • Updated
How to use UICHEOL-HWANG/malicious-url-detection with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="UICHEOL-HWANG/malicious-url-detection") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("UICHEOL-HWANG/malicious-url-detection")
model = AutoModelForSequenceClassification.from_pretrained("UICHEOL-HWANG/malicious-url-detection", device_map="auto")base_model : distilbert/distilbert-base-uncased
tune parameters
batch_size : 64
epocs : 5
learning_rate : 2e-5
weight_decay : 0.01
| Step | Training Loss | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|
| 200 | 0.024300 | 0.453651 | 0.929750 | 0.928860 |
| 400 | 0.016700 | 0.543543 | 0.917750 | 0.916868 |
| 600 | 0.007600 | 0.604909 | 0.921250 | 0.921414 |
| 800 | 0.008500 | 0.588405 | 0.922750 | 0.922533 |
| 1000 | 0.007300 | 0.618596 | 0.925500 | 0.925138 |
| 1200 | 0.006300 | 0.628956 | 0.923250 | 0.922644 |
2025.02.17 기준
Dacon 순위 24위Base model
distilbert/distilbert-base-uncased