YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

DistilBERT Subject Classifier

A lightweight, single‐label text‐classification model built on DistilBERT to assign one of 19 high‑level academic or professional subjects to an input text.


Model Overview

  • Architecture: DistilBertForSequenceClassification
  • Hidden Size: 768
  • Intermediate (FFN) Size: 3072
  • Heads / Layers: 12 heads × 6 layers
  • Dropout:
    • Attention dropout: 0.1
    • Sequence‐classification dropout: 0.2
  • Activation: GELU
  • Max Sequence Length: 512 tokens

Label Mapping

ID Label ID Label
0 english 10 math
1 music 11 philosophy
2 environmental science 12 psychology
3 history 13 engineering
4 art and design 14 biology
5 political science 15 sociology
6 computer science 16 chemistry
7 business/management 17 economics
8 medicine/health sciences 18 physics
9 law

Configuration Highlights

{
  "model_type": "distilbert",
  "initializer_range": 0.02,
  "problem_type": "single_label_classification",
  "torch_dtype": "float32",
  "transformers_version": "4.49.0"
}
Downloads last month
4
Safetensors
Model size
67M params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support