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ROS-text-classification

Text Classification
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Safetensors
bert
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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: ROS-text-classification
    results: []

ROS-text-classification

This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8096
  • Balanced Accuracy: 0.7524

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Balanced Accuracy
1.4134 1.0 139 1.2061 0.5871
0.7846 2.0 278 0.9400 0.6932
0.6999 3.0 417 0.8096 0.7524
0.3644 4.0 556 0.8431 0.7721
0.3832 5.0 695 0.9038 0.7594
0.2631 6.0 834 1.0126 0.7800

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1