README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - akahana/GlotCC-V1-jav-Latn
metrics:
  - accuracy
model-index:
  - name: mini-roberta-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: 0.15905819453012543

mini-roberta-javanese

This model is a fine-tuned version of on the akahana/GlotCC-V1-jav-Latn default dataset. It achieves the following results on the evaluation set:

• Loss: 6.0607
• Accuracy: 0.1591

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: 128
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 30.0
• 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