readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - indonlu
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-indonesian-sentiment-analysis-smsa
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: indonlu
        type: indonlu
        args: smsa
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9349206349206349
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # roberta-base-indonesian-sentiment-analysis-smsa
  
  This model is a fine-tuned version of [flax-community/indonesian-roberta-base](https://huggingface.co/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
  