readme: ---
  
  model-index:
  - name: qa-indo-math-k
  ---
  
  <!-- 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. -->
  
  # qa-indo-math-k
  
  This model was trained from scratch on an unkown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8801
  
  ## 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: 10
  - eval_batch_size: 10
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 127  | 0.7652          |
  | No log        | 2.0   | 254  | 0.7520          |
  | No log        | 3.0   | 381  | 0.7681          |
  | 0.9618        | 4.0   | 508  | 0.7337          |
  | 0.9618        | 5.0   | 635  | 0.7560          |
  | 0.9618        | 6.0   | 762  | 0.7397          |
  | 0.9618        | 7.0   | 889  | 0.7298          |
  | 0.6652        | 8.0   | 1016 | 0.7891          |
  | 0.6652        | 9.0   | 1143 | 0.7874          |
  | 0.6652        | 10.0  | 1270 | 0.7759          |
  | 0.6652        | 11.0  | 1397 | 0.7505          |
  | 0.6174        | 12.0  | 1524 | 0.7838          |
  | 0.6174        | 13.0  | 1651 | 0.7878          |
  | 0.6174        | 14.0  | 1778 | 0.8028          |
  | 0.6174        | 15.0  | 1905 | 0.8154          |
  | 0.5733        | 16.0  | 2032 | 0.8131          |
  | 0.5733        | 17.0  | 2159 | 0.8278          |
  | 0.5733        | 18.0  | 2286 | 0.8308          |
  | 0.5733        | 19.0  | 2413 | 0.8433          |
  | 0.5378        | 20.0  | 2540 | 0.8303          |
  | 0.5378        | 21.0  | 2667 | 0.8352          |
  | 0.5378        | 22.0  | 2794 | 0.8369          |
  | 0.5378        | 23.0  | 2921 | 0.8518          |
  | 0.5095        | 24.0  | 3048 | 0.8749          |
  | 0.5095        | 25.0  | 3175 | 0.8533          |
  | 0.5095        | 26.0  | 3302 | 0.8547          |
  | 0.5095        | 27.0  | 3429 | 0.8844          |
  | 0.4856        | 28.0  | 3556 | 0.8752          |
  | 0.4856        | 29.0  | 3683 | 0.8804          |
  | 0.4856        | 30.0  | 3810 | 0.8801          |
  
  
  ### Framework versions
  
  - Transformers 4.6.1
  - Pytorch 1.7.0
  - Datasets 1.11.0
  - Tokenizers 0.10.3
  