Text Classification
Transformers
Joblib
English
cybersecurity
industrial-control-systems
bert
from-scratch
synthetic-data
Instructions to use ARotting/protocol-guardian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ARotting/protocol-guardian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ARotting/protocol-guardian")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ARotting/protocol-guardian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 845 Bytes
aad0df8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | {
"model": "Protocol Guardian MiniLM Linear",
"base_model": "sentence-transformers/all-MiniLM-L6-v2",
"embedding_dimensions": 384,
"linear_head_parameters": 385,
"selected_c": 0.3,
"validation": {
"accuracy": 0.8175,
"precision": 0.7343173431734318,
"recall": 0.995,
"f1": 0.8450106157112527,
"confusion_matrix": [
[
256,
144
],
[
2,
398
]
],
"examples": 800
},
"test": {
"accuracy": 0.8858333333333334,
"precision": 1.0,
"recall": 0.7716666666666666,
"f1": 0.8711194731890874,
"confusion_matrix": [
[
600,
0
],
[
137,
463
]
],
"examples": 1200
},
"test_split": "1200 examples from a third, unseen template family"
} |