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metadata
license: mit
base_model: indolem/indobert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: indonesian-brand-indoBERT-finetuned
    results: []

indonesian-brand-indoBERT-finetuned

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: 0.6848
  • Accuracy: 0.8601
  • Precision: 0.8601
  • Recall: 0.8601
  • F1: 0.8601

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
  • lr_scheduler_warmup_ratio: 0.01
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
No log 1.0 304 0.4935 0.8132 0.8132 0.8132 0.8132
0.5911 2.0 608 0.4046 0.8362 0.8362 0.8362 0.8362
0.5911 3.0 912 0.4873 0.8305 0.8305 0.8305 0.8305
0.3204 4.0 1216 0.4774 0.8560 0.8560 0.8560 0.8560
0.2154 5.0 1520 0.5759 0.8486 0.8486 0.8486 0.8486
0.2154 6.0 1824 0.6334 0.8568 0.8568 0.8568 0.8568
0.1454 7.0 2128 0.6848 0.8601 0.8601 0.8601 0.8601
0.1454 8.0 2432 0.7325 0.8560 0.8560 0.8560 0.8560
0.0982 9.0 2736 0.7782 0.8568 0.8568 0.8568 0.8568
0.0729 10.0 3040 0.7979 0.8584 0.8584 0.8584 0.8584

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2