---
tags:
- generated_from_trainer
datasets:
- akahana/GlotCC-V1-jav-Latn
metrics:
- accuracy
model-index:
- name: smallbert-javanese
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: akahana/GlotCC-V1-jav-Latn default
      type: akahana/GlotCC-V1-jav-Latn
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.1417211592798902
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# smallbert-javanese

This model is a fine-tuned version of [](https://huggingface.co/) on the akahana/GlotCC-V1-jav-Latn default dataset.
It achieves the following results on the evaluation set:
- Loss: 6.2400
- Accuracy: 0.1417

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1