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---
library_name: transformers
tags: []
---
## Fine-tuned roberta-base for detecting paragraphs with eHRAF-assigned two-digit id '900'
## Description
This is a fine tuned roberta-base model for detecting whether paragraphs drawn from ethnographic source material classified under the main subject 'Language and Communication' is more specifically about '900'.
## Usage
The easiest way to use this model at inference time is with the HF pipelines API.
```python
from transformers import pipeline
classifier = pipeline("text-classification", model="gptmurdock/classifier-900")
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 | 98.0 |
| Recall | 97.9 |
| F1 | 97.9 |
|