readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: madatnlp/ke-t5-math-py
    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/ke-t5-math-py
  
  This model is a fine-tuned version of [KETI-AIR/ke-t5-base-ko](https://huggingface.co/KETI-AIR/ke-t5-base-ko) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.1203
  - Validation Loss: 0.4336
  - Epoch: 47
  
  ## 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': 'Adam', 'learning_rate': 0.001, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 2.0197     | 1.2886          | 0     |
  | 1.5642     | 1.1261          | 1     |
  | 1.3713     | 1.0296          | 2     |
  | 1.2555     | 0.9905          | 3     |
  | 1.1708     | 0.9628          | 4     |
  | 1.1161     | 0.9133          | 5     |
  | 1.0704     | 0.8994          | 6     |
  | 1.0297     | 0.8911          | 7     |
  | 0.9898     | 0.8570          | 8     |
  | 0.9608     | 0.8497          | 9     |
  | 0.9326     | 0.8359          | 10    |
  | 0.9089     | 0.8387          | 11    |
  | 0.8882     | 0.8083          | 12    |
  | 0.8627     | 0.8154          | 13    |
  | 0.8467     | 0.8058          | 14    |
  | 0.8314     | 0.7905          | 15    |
  | 0.8071     | 0.7852          | 16    |
  | 0.7975     | 0.7873          | 17    |
  | 0.8021     | 0.7926          | 18    |
  | 0.7754     | 0.7858          | 19    |
  | 0.7598     | 0.7941          | 20    |
  | 0.7463     | 0.7769          | 21    |
  | 0.7266     | 0.7594          | 22    |
  | 0.7092     | 0.7744          | 23    |
  | 0.6986     | 0.7611          | 24    |
  | 0.6818     | 0.7592          | 25    |
  | 0.6775     | 0.7718          | 26    |
  | 0.6689     | 0.7685          | 27    |
  | 0.6474     | 0.7554          | 28    |
  | 0.6328     | 0.7601          | 29    |
  | 0.6050     | 0.7042          | 30    |
  | 0.5296     | 0.5711          | 31    |
  | 0.4310     | 0.5227          | 32    |
  | 0.3729     | 0.4740          | 33    |
  | 0.3353     | 0.4552          | 34    |
  | 0.3006     | 0.4375          | 35    |
  | 0.2750     | 0.4233          | 36    |
  | 0.2494     | 0.4487          | 37    |
  | 0.2287     | 0.4294          | 38    |
  | 0.2160     | 0.4119          | 39    |
  | 0.1980     | 0.4309          | 40    |
  | 0.1837     | 0.4182          | 41    |
  | 0.1699     | 0.4045          | 42    |
  | 0.1577     | 0.4065          | 43    |
  | 0.1498     | 0.4247          | 44    |
  | 0.1392     | 0.4102          | 45    |
  | 0.1282     | 0.4274          | 46    |
  | 0.1203     | 0.4336          | 47    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - TensorFlow 2.8.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  