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sentiment

This model is a fine-tuned version of naufalihsan/indonesian-sbert-large on the indonlu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4450
  • Accuracy: 0.95
  • Precision: 0.9500
  • Recall: 0.95
  • F1: 0.9496

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: 40
  • eval_batch_size: 40
  • 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 1.0 275 0.2837 0.9405 0.9427 0.9405 0.9396
0.0501 2.0 550 0.1966 0.9460 0.9468 0.9460 0.9458
0.0501 3.0 825 0.2927 0.9437 0.9435 0.9437 0.9427
0.0369 4.0 1100 0.3666 0.9460 0.9459 0.9460 0.9456
0.0369 5.0 1375 0.3579 0.9468 0.9465 0.9468 0.9465
0.0098 6.0 1650 0.4497 0.9476 0.9479 0.9476 0.9471
0.0098 7.0 1925 0.4308 0.95 0.9501 0.95 0.9496
0.0012 8.0 2200 0.4402 0.95 0.9499 0.95 0.9496
0.0012 9.0 2475 0.4429 0.95 0.9500 0.95 0.9496
0.0007 10.0 2750 0.4450 0.95 0.9500 0.95 0.9496

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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Dataset used to train AptaArkana/indonesian_sentiment_sbert_base

Evaluation results