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metadata
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: indobert-finetuned-sentiment-happiness-index
    results: []
widget:
  - text: Aku suka makan bakso
    example_title: Sentiment Analysis
language:
  - id
pipeline_tag: text-classification

indobert-finetuned-sentiment-happiness-index

This model is a fine-tuned version of indobenchmark/indobert-base-p1 on an own private dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4094
  • Accuracy: 0.8048

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 Accuracy
No log 1.0 270 0.5214 0.7900
0.5321 2.0 540 0.6425 0.7475
0.5321 3.0 810 0.7702 0.7835
0.1711 4.0 1080 1.0106 0.7937
0.1711 5.0 1350 1.2141 0.7891
0.0508 6.0 1620 1.3340 0.7965
0.0508 7.0 1890 1.3483 0.8030
0.0133 8.0 2160 1.3591 0.8085
0.0133 9.0 2430 1.4149 0.8057
0.0055 10.0 2700 1.4094 0.8048

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3