---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-bib-lang-grammar
  results: []
datasets:
- RickBrannan/categorize_bib_lang_grammar
language:
- en
---

# distilbert-base-uncased-finetuned-bib-lang-grammar

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the dataset [RickBrannan/categorize_bib_lang_grammar](https://huggingface.co/datasets/RickBrannan/categorize_bib_lang_grammar).

## Intended uses & limitations

This model is intended to be used to locate discussions that utilize grammatical terminology within resources like biblical commentaries or study notes.

## Training and evaluation data

This model is trained on [RickBrannan/categorize_bib_lang_grammar](https://huggingface.co/datasets/RickBrannan/categorize_bib_lang_grammar), which is a collection of 2,700+ sentences categorized as `NOT-GRAMMAR` or `GRAMMAR`.

For details on the dataset and its sources, see the [Dataset Card](https://huggingface.co/datasets/RickBrannan/categorize_bib_lang_grammar).

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2

### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cpu
- Datasets 3.1.0
- Tokenizers 0.20.3