Downloads · 30 days
3
10% of all-time downloads
classifier-main_subjects_technology
gptmurdock/classifier-main_subjects_technology
classifier-main_subjects_technology is a text classification model from gptmurdock. Use it when you need a label for a piece of text. It is set up for transformers.
This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material are about 'Technology and Material Culture'.
All-time downloads
30
Public
Parameters
125M
499 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors499 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Sep 17, 2024
- Updated
- Sep 19, 2024
- SHA
- 9e5233ad
Try a prompt
Model card
From the Hugging Face model README
Fine-tuned roberta-base for detecting paragraphs on the topic of 'Technology and Material Culture'
Description
This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material are about 'Technology and Material Culture'.
Usage
The easiest way to use this model at inference time is with the HF pipelines API.
from transformers import pipeline
classifier = pipeline("text-classification", model="gptmurdock/classifier-main_subjects_technology")
classifier("Example text to classify")
Training data
...
Training procedure
...
We use a 60-20-20 train-val-test split, and fine-tuned roberta-base for 5 epochs (lr = 2e-5, batch size = 40).
Evaluation
Evals on the test set are reported below.
| Metric | Value |
|---|---|
| Precision | 93.6 |
| Recall | 93.7 |
| F1 | 93.6 |
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Sep 17, 2024
- Updated
- Sep 19, 2024