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End of training
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metadata
license: mit
base_model: w11wo/indo-roberta-small
tags:
  - generated_from_trainer
datasets:
  - indonlu
metrics:
  - accuracy
model-index:
  - name: indo-roberta-small-finetuned-indonlu-smsa
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: indonlu
          type: indonlu
          config: smsa
          split: validation
          args: smsa
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.888095238095238

indo-roberta-small-finetuned-indonlu-smsa

This model is a fine-tuned version of w11wo/indo-roberta-small on the indonlu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4497
  • Accuracy: 0.8881

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 172 0.6502 0.7143
No log 2.0 344 0.4720 0.8127
0.6168 3.0 516 0.4511 0.8357
0.6168 4.0 688 0.3825 0.8540
0.6168 5.0 860 0.3655 0.8595
0.2954 6.0 1032 0.3672 0.8683
0.2954 7.0 1204 0.3839 0.8746
0.2954 8.0 1376 0.4220 0.8706
0.1328 9.0 1548 0.4497 0.8881
0.1328 10.0 1720 0.4455 0.8865

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2