readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: madatnlp/kor-math-roberta-finetune
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # madatnlp/kor-math-roberta-finetune
  
  This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.3205
  - Validation Loss: 1.1407
  - Epoch: 26
  
  ## 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:
  - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  - training_precision: mixed_bfloat16
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 3.4242     | 2.0873          | 0     |
  | 1.9159     | 1.6264          | 1     |
  | 1.5933     | 1.4521          | 2     |
  | 1.3806     | 1.3584          | 3     |
  | 1.2487     | 1.2904          | 4     |
  | 1.1464     | 1.2388          | 5     |
  | 1.0552     | 1.2076          | 6     |
  | 0.9889     | 1.1818          | 7     |
  | 0.9118     | 1.1607          | 8     |
  | 0.8459     | 1.1349          | 9     |
  | 0.7838     | 1.1193          | 10    |
  | 0.7389     | 1.1193          | 11    |
  | 0.6864     | 1.1080          | 12    |
  | 0.6495     | 1.1001          | 13    |
  | 0.6103     | 1.1001          | 14    |
  | 0.5795     | 1.0990          | 15    |
  | 0.5436     | 1.0954          | 16    |
  | 0.5136     | 1.0997          | 17    |
  | 0.4906     | 1.0954          | 18    |
  | 0.4565     | 1.1021          | 19    |
  | 0.4347     | 1.1075          | 20    |
  | 0.4131     | 1.1075          | 21    |
  | 0.3924     | 1.1220          | 22    |
  | 0.3741     | 1.1298          | 23    |
  | 0.3549     | 1.1352          | 24    |
  | 0.3395     | 1.1286          | 25    |
  | 0.3205     | 1.1407          | 26    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - TensorFlow 2.8.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  