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distilbert-attractions
VictorTishkevich/distilbert-attractions
distilbert-attractions is a text classification model from VictorTishkevich. Use it when you need a label for a piece of text. It is set up for autogluon.
This model classifies text descriptions of US tourist attractions as Natural or Human-made. It fine-tunes a pretrained distilbert-base-uncased model with AutoGluon MultiModal.
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Public
Updated Sep 23, 2026
Repo size
266 MB
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.ckpt265 MB · 100%
At a glance
- Task
- Text Classification
- Library
- autogluon
- Access
- Public
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026
- SHA
- 206b7259
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Model card
From the Hugging Face model README
US Attractions Classifier
This model classifies text descriptions of US tourist attractions as Natural or Human-made. It fine-tunes a pretrained distilbert-base-uncased model with AutoGluon MultiModal.
Inputs and outputs
Supply a pandas DataFrame with a text column containing attraction descriptions.
predict() returns Natural or Human-made.
| Label | Meaning |
|---|---|
0 | Natural |
1 | Human-made |
Data and training
Source: US Attractions Dataset.
| Training setting | Recorded value |
|---|---|
| Framework | AutoGluon MultiModal 1.6.1 |
| Text backbone | distilbert-base-uncased |
| Selection metric | Validation accuracy |
| Seed | 24679 |
| Max epochs | 5 |
| Learning rate | 2e-5 |
| Fine-tuning mode | norm_fit (62,978 / 66,364,418 trainable parameters) |
Evaluation
| Test metric | Value |
|---|---|
| Accuracy | 0.9333 |
| Weighted F1 | 0.9333 |
- Task
- Text Classification
- Library
- autogluon
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026