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johannawawi/v5_balanced_dataset_fine-tuning-java-indo-sentiment-analysist-3-class
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metadata
library_name: transformers
license: mit
base_model: w11wo/indonesian-roberta-base-sentiment-classifier
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: results_final
    results: []

results_final

This model is a fine-tuned version of w11wo/indonesian-roberta-base-sentiment-classifier on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3507
  • Accuracy: 0.9056
  • F1 Macro: 0.9055
  • F1 Weighted: 0.9055
  • Precision Macro: 0.9057
  • Recall Macro: 0.9056
  • Precision Weighted: 0.9057
  • Recall Weighted: 0.9056

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: 4e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.2
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Macro F1 Weighted Precision Macro Recall Macro Precision Weighted Recall Weighted
0.4024 1.8519 500 0.2951 0.9 0.9002 0.9002 0.9011 0.9000 0.9011 0.9
0.3394 3.7037 1000 0.3384 0.8944 0.8946 0.8946 0.8960 0.8944 0.8960 0.8944
0.2395 5.5556 1500 0.3507 0.9056 0.9055 0.9055 0.9057 0.9056 0.9057 0.9056
0.2222 7.4074 2000 0.3621 0.9 0.9000 0.9000 0.9003 0.9 0.9003 0.9
0.1813 9.2593 2500 0.3718 0.8963 0.8963 0.8963 0.8963 0.8963 0.8963 0.8963

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 2.14.4
  • Tokenizers 0.21.1