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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - indonlu
metrics:
  - accuracy
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: distilled-indobert-classification
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: indonlu
          type: indonlu
          args: smsa
        metrics:
          - type: accuracy
            value: 0.9015873015873016
            name: Accuracy
          - type: f1
            value: 0.9014926755197933
            name: F1

distilled-indobert-classification

This model is a fine-tuned version of distilbert-base-uncased on the indonlu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6015
  • Accuracy: 0.9016
  • F1: 0.9015

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: 6e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
1.0427 1.0 688 0.6306 0.8683 0.8684
0.5332 2.0 1376 0.5621 0.8794 0.8779
0.3021 3.0 2064 0.6785 0.8905 0.8896
0.1851 4.0 2752 0.6085 0.8968 0.8959
0.1152 5.0 3440 0.6015 0.9016 0.9015

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.10.0+cu111
  • Datasets 2.0.0
  • Tokenizers 0.11.6