readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: codet5-kormath
    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. -->
  
  # codet5-kormath
  
  This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.1215
  - Validation Loss: 0.5475
  - Epoch: 43
  
  ## 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: mixed_bfloat16
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 6.8077     | 3.6916          | 0     |
  | 3.3252     | 2.3874          | 1     |
  | 2.2389     | 1.7377          | 2     |
  | 1.6852     | 1.3997          | 3     |
  | 1.3617     | 1.1785          | 4     |
  | 1.1875     | 1.0796          | 5     |
  | 1.0887     | 1.0150          | 6     |
  | 1.0234     | 0.9669          | 7     |
  | 0.9709     | 0.9350          | 8     |
  | 0.9292     | 0.9016          | 9     |
  | 0.8982     | 0.8763          | 10    |
  | 0.8653     | 0.8565          | 11    |
  | 0.8389     | 0.8378          | 12    |
  | 0.8094     | 0.8241          | 13    |
  | 0.7828     | 0.8078          | 14    |
  | 0.7631     | 0.7945          | 15    |
  | 0.7386     | 0.7856          | 16    |
  | 0.7209     | 0.7749          | 17    |
  | 0.7039     | 0.7703          | 18    |
  | 0.6858     | 0.7708          | 19    |
  | 0.6718     | 0.7705          | 20    |
  | 0.6544     | 0.7710          | 21    |
  | 0.6477     | 0.7728          | 22    |
  | 0.6289     | 0.7590          | 23    |
  | 0.6102     | 0.7616          | 24    |
  | 0.5966     | 0.7644          | 25    |
  | 0.5773     | 0.7559          | 26    |
  | 0.5597     | 0.7609          | 27    |
  | 0.5384     | 0.7823          | 28    |
  | 0.5256     | 0.7263          | 29    |
  | 0.4780     | 0.6671          | 30    |
  | 0.4328     | 0.6591          | 31    |
  | 0.3844     | 0.5918          | 32    |
  | 0.3366     | 0.5852          | 33    |
  | 0.3036     | 0.5633          | 34    |
  | 0.2746     | 0.5566          | 35    |
  | 0.2486     | 0.5644          | 36    |
  | 0.2286     | 0.5293          | 37    |
  | 0.2023     | 0.5256          | 38    |
  | 0.1870     | 0.5276          | 39    |
  | 0.1638     | 0.5272          | 40    |
  | 0.1479     | 0.5642          | 41    |
  | 0.1386     | 0.5482          | 42    |
  | 0.1215     | 0.5475          | 43    |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - TensorFlow 2.8.0
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  