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Librarian Bot: Add base_model information to model
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metadata
license: mit
tags:
  - generated_from_trainer
datasets:
  - indonlu
metrics:
  - accuracy
base_model: flax-community/indonesian-roberta-base
model-index:
  - name: roberta-base-indonesian-sentiment-analysis-smsa
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: indonlu
          type: indonlu
          args: smsa
        metrics:
          - type: accuracy
            value: 0.9349206349206349
            name: Accuracy

roberta-base-indonesian-sentiment-analysis-smsa

This model is a fine-tuned version of flax-community/indonesian-roberta-base on the indonlu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4252
  • Accuracy: 0.9349

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_steps: 2000
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7582 1.0 688 0.3280 0.8786
0.3225 2.0 1376 0.2398 0.9206
0.2057 3.0 2064 0.2574 0.9230
0.1642 4.0 2752 0.2820 0.9302
0.1266 5.0 3440 0.3344 0.9317
0.0608 6.0 4128 0.3543 0.9341
0.058 7.0 4816 0.4252 0.9349
0.0315 8.0 5504 0.4736 0.9310
0.0166 9.0 6192 0.4649 0.9349
0.0143 10.0 6880 0.4648 0.9341

Framework versions

  • Transformers 4.14.1
  • Pytorch 1.10.0+cu111
  • Datasets 1.16.1
  • Tokenizers 0.10.3