readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: roberta-indonlu-smsa-google-review
    results: []
  ---
  
  <!-- 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-indonlu-smsa-google-review
  
  This model is a fine-tuned version of [flax-community/indonesian-roberta-base](https://huggingface.co/flax-community/indonesian-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4822
  - Accuracy: 0.9286
  - F1: 0.8700
  - Precision: 0.8835
  - Recall: 0.8575
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.3335        | 1.0   | 2254  | 0.3628          | 0.9113   | 0.8292 | 0.8068    | 0.8569 |
  | 0.2709        | 2.0   | 4508  | 0.3240          | 0.9221   | 0.8503 | 0.8418    | 0.8605 |
  | 0.2174        | 3.0   | 6762  | 0.3763          | 0.9218   | 0.8426 | 0.8335    | 0.8598 |
  | 0.1528        | 4.0   | 9016  | 0.3910          | 0.9202   | 0.8543 | 0.8388    | 0.8715 |
  | 0.1017        | 5.0   | 11270 | 0.3852          | 0.9260   | 0.8626 | 0.8804    | 0.8464 |
  | 0.0993        | 6.0   | 13524 | 0.4577          | 0.9263   | 0.8645 | 0.8869    | 0.8451 |
  | 0.0712        | 7.0   | 15778 | 0.4901          | 0.9249   | 0.8691 | 0.8809    | 0.8584 |
  | 0.0571        | 8.0   | 18032 | 0.5021          | 0.9265   | 0.8646 | 0.8571    | 0.8739 |
  | 0.0494        | 9.0   | 20286 | 0.4822          | 0.9286   | 0.8700 | 0.8835    | 0.8575 |
  | 0.0274        | 10.0  | 22540 | 0.4945          | 0.9272   | 0.8674 | 0.8755    | 0.8596 |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  