readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - indonlu
  metrics:
  - accuracy
  model-index:
  - name: bert-base-indonesian-1.5G-finetuned-sentiment-analysis-smsa
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: indonlu
        type: indonlu
        args: smsa
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9373015873015873
  language: id
  widget:
  - text: "Saya mengapresiasi usaha anda"
  ---
  
  <!-- 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. -->
  
  # bert-base-indonesian-1.5G-finetuned-sentiment-analysis-smsa
  
  This model is a fine-tuned version of [cahya/bert-base-indonesian-1.5G](https://huggingface.co/cahya/bert-base-indonesian-1.5G) on the indonlu dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3390
  - Accuracy: 0.9373
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.2864        | 1.0   | 688  | 0.2154          | 0.9286   |
  | 0.1648        | 2.0   | 1376 | 0.2238          | 0.9357   |
  | 0.0759        | 3.0   | 2064 | 0.3351          | 0.9365   |
  | 0.044         | 4.0   | 2752 | 0.3390          | 0.9373   |
  | 0.0308        | 5.0   | 3440 | 0.4346          | 0.9365   |
  | 0.0113        | 6.0   | 4128 | 0.4708          | 0.9365   |
  | 0.006         | 7.0   | 4816 | 0.5533          | 0.9325   |
  | 0.0047        | 8.0   | 5504 | 0.5888          | 0.9310   |
  | 0.0001        | 9.0   | 6192 | 0.5961          | 0.9333   |
  | 0.0           | 10.0  | 6880 | 0.5992          | 0.9357   |
  
  
  ### Framework versions
  
  - Transformers 4.14.1
  - Pytorch 1.10.0+cu111
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  