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Training fold 3
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metadata
license: mit
base_model: ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: best_berita_bert_model_fold_3
    results: []

best_berita_bert_model_fold_3

This model is a fine-tuned version of ayameRushia/bert-base-indonesian-1.5G-sentiment-analysis-smsa on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1732
  • Accuracy: 0.9808
  • Precision: 0.9809
  • Recall: 0.9811
  • F1: 0.9809

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: 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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.5469 1.0 601 0.2814 0.9409 0.9416 0.9414 0.9410
0.21 2.0 1202 0.1697 0.9600 0.9602 0.9605 0.9600
0.1002 3.0 1803 0.2227 0.9667 0.9674 0.9673 0.9666
0.0847 4.0 2404 0.2771 0.9584 0.9599 0.9592 0.9581
0.029 5.0 3005 0.1732 0.9808 0.9809 0.9811 0.9809
0.0095 6.0 3606 0.2415 0.9734 0.9737 0.9738 0.9733
0.0134 7.0 4207 0.2048 0.9767 0.9769 0.9771 0.9766
0.0001 8.0 4808 0.2916 0.9692 0.9697 0.9698 0.9691
0.0039 9.0 5409 0.2201 0.9784 0.9786 0.9787 0.9784
0.0 10.0 6010 0.2293 0.9742 0.9745 0.9746 0.9742

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1