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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: madatnlp/mt5-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. -->
# madatnlp/mt5-kormath
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7119
- Validation Loss: 1.1299
- Epoch: 61
## 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 |
|:----------:|:---------------:|:-----:|
| 17.9929 | 5.9287 | 0 |
| 5.4802 | 3.9942 | 1 |
| 4.1718 | 3.2517 | 2 |
| 3.5750 | 2.9586 | 3 |
| 3.1535 | 2.4970 | 4 |
| 2.8665 | 2.4626 | 5 |
| 2.6682 | 2.3795 | 6 |
| 2.5323 | 2.2238 | 7 |
| 2.4057 | 2.0684 | 8 |
| 2.3107 | 2.2033 | 9 |
| 2.2501 | 1.8339 | 10 |
| 2.1089 | 1.9064 | 11 |
| 2.0741 | 2.0256 | 12 |
| 1.9868 | 1.8107 | 13 |
| 1.9719 | 1.7157 | 14 |
| 1.8762 | 1.6966 | 15 |
| 1.8814 | 1.6580 | 16 |
| 1.8052 | 1.6043 | 17 |
| 1.7567 | 1.6572 | 18 |
| 1.7209 | 1.5485 | 19 |
| 1.7347 | 1.6464 | 20 |
| 1.6760 | 1.5892 | 21 |
| 1.6286 | 1.5765 | 22 |
| 1.6124 | 1.7408 | 23 |
| 1.5683 | 1.4875 | 24 |
| 1.5814 | 1.4448 | 25 |
| 1.5306 | 1.4902 | 26 |
| 1.5121 | 1.5133 | 27 |
| 1.4869 | 1.4217 | 28 |
| 1.4539 | 1.5602 | 29 |
| 1.4650 | 1.4699 | 30 |
| 1.4508 | 1.4319 | 31 |
| 1.3910 | 1.5975 | 32 |
| 1.3758 | 1.4031 | 33 |
| 1.3550 | 1.4295 | 34 |
| 1.3405 | 1.3804 | 35 |
| 1.3144 | 1.4202 | 36 |
| 1.3136 | 1.5135 | 37 |
| 1.2617 | 1.4790 | 38 |
| 1.2260 | 1.4108 | 39 |
| 1.2348 | 1.3108 | 40 |
| 1.2019 | 1.1461 | 41 |
| 1.1775 | 1.2509 | 42 |
| 1.1690 | 1.2179 | 43 |
| 1.1318 | 1.2483 | 44 |
| 1.1013 | 1.0815 | 45 |
| 1.0735 | 1.2135 | 46 |
| 1.0439 | 1.1260 | 47 |
| 1.0182 | 1.1993 | 48 |
| 0.9971 | 1.0797 | 49 |
| 0.9583 | 1.2587 | 50 |
| 0.9505 | 1.0793 | 51 |
| 0.9366 | 1.0501 | 52 |
| 0.9170 | 1.1476 | 53 |
| 0.8741 | 1.0560 | 54 |
| 0.8558 | 1.0024 | 55 |
| 0.8394 | 0.9604 | 56 |
| 0.8203 | 1.2700 | 57 |
| 0.7938 | 1.1081 | 58 |
| 0.7800 | 1.0198 | 59 |
| 0.7378 | 1.1748 | 60 |
| 0.7119 | 1.1299 | 61 |
### Framework versions
- Transformers 4.18.0
- TensorFlow 2.8.0
- Datasets 2.2.0
- Tokenizers 0.12.1
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