bdc2024-indobert-2 / README.md
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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: bdc2024-indobert-2
    results: []

bdc2024-indobert-2

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5554
  • Accuracy: 0.9331
  • Balanced Accuracy: 0.8724
  • Precision: 0.9353
  • Recall: 0.9331
  • F1: 0.9289

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: 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: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy Balanced Accuracy Precision Recall F1
No log 1.0 483 0.5108 0.9197 0.8454 0.9195 0.9197 0.9132
0.0773 2.0 966 0.5374 0.9235 0.8668 0.9266 0.9235 0.9196
0.0374 3.0 1449 0.5451 0.9331 0.8689 0.9359 0.9331 0.9281
0.0242 4.0 1932 0.5567 0.9331 0.8726 0.9353 0.9331 0.9288
0.0162 5.0 2415 0.5554 0.9331 0.8724 0.9353 0.9331 0.9289

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.13.3