readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - tydiqa
  model-index:
  - name: indobert-finetune-tydiqa-transfer-indoqa
    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. -->
  
  # indobert-finetune-tydiqa-transfer-indoqa
  
  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the tydiqa dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3210
  
  ## 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: 24
  - eval_batch_size: 24
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 3.162         | 1.0   | 241  | 3.2961          |
  | 1.9671        | 2.0   | 482  | 2.4509          |
  | 1.457         | 3.0   | 723  | 2.3005          |
  | 1.2349        | 4.0   | 964  | 2.2628          |
  | 1.0681        | 5.0   | 1205 | 2.1436          |
  | 0.9338        | 6.0   | 1446 | 2.1978          |
  | 0.8523        | 7.0   | 1687 | 2.2780          |
  | 0.7909        | 8.0   | 1928 | 2.2481          |
  | 0.725         | 9.0   | 2169 | 2.2912          |
  | 0.6977        | 10.0  | 2410 | 2.3210          |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  