madatnlp/mt5-kormath
This model is a fine-tuned version of 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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