pertama / README.md
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metadata
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
  - generated_from_trainer
model-index:
  - name: pertama
    results: []

pertama

This model is a fine-tuned version of indobenchmark/indobert-large-p2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.4507
  • F1 macro: 0.4131
  • Weighted: 0.5840
  • Balanced accuracy: 0.5423

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 14

Training results

Training Loss Epoch Step Validation Loss F1 macro Weighted Balanced accuracy
1.3416 1.0 154 1.5603 0.2942 0.3462 0.4357
0.941 2.0 308 1.3408 0.3530 0.5202 0.4807
0.6965 3.0 462 1.3731 0.3747 0.5629 0.5101
0.4375 4.0 616 1.3137 0.3904 0.5961 0.5002
0.2491 5.0 770 1.5577 0.3772 0.5930 0.4978
0.0793 6.0 924 2.1326 0.3923 0.5382 0.5401
0.0488 7.0 1078 2.2000 0.3861 0.5483 0.5243
0.0206 8.0 1232 2.1568 0.3914 0.5873 0.5096
0.0243 9.0 1386 2.2272 0.4118 0.5851 0.5457
0.0126 10.0 1540 2.3494 0.4029 0.5885 0.5346
0.0449 11.0 1694 2.2914 0.4115 0.6037 0.5387
0.0023 12.0 1848 2.5714 0.3962 0.5675 0.5334
0.0023 13.0 2002 2.4491 0.4155 0.5878 0.5400
0.0024 14.0 2156 2.4507 0.4131 0.5840 0.5423

Framework versions

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