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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: madatnlp/mt5-kormath |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# madatnlp/mt5-kormath |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.7119 |
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- Validation Loss: 1.1299 |
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- Epoch: 61 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'Adam', 'learning_rate': 0.001, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
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- training_precision: mixed_bfloat16 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 17.9929 | 5.9287 | 0 | |
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| 5.4802 | 3.9942 | 1 | |
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| 4.1718 | 3.2517 | 2 | |
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| 3.5750 | 2.9586 | 3 | |
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| 3.1535 | 2.4970 | 4 | |
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| 2.8665 | 2.4626 | 5 | |
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| 2.6682 | 2.3795 | 6 | |
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| 2.5323 | 2.2238 | 7 | |
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| 2.4057 | 2.0684 | 8 | |
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| 2.3107 | 2.2033 | 9 | |
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| 2.2501 | 1.8339 | 10 | |
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| 2.1089 | 1.9064 | 11 | |
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| 2.0741 | 2.0256 | 12 | |
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| 1.9868 | 1.8107 | 13 | |
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| 1.9719 | 1.7157 | 14 | |
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| 1.8762 | 1.6966 | 15 | |
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| 1.8814 | 1.6580 | 16 | |
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| 1.8052 | 1.6043 | 17 | |
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| 1.7567 | 1.6572 | 18 | |
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| 1.7209 | 1.5485 | 19 | |
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| 1.7347 | 1.6464 | 20 | |
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| 1.6760 | 1.5892 | 21 | |
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| 1.6286 | 1.5765 | 22 | |
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| 1.6124 | 1.7408 | 23 | |
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| 1.5683 | 1.4875 | 24 | |
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| 1.5814 | 1.4448 | 25 | |
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| 1.5306 | 1.4902 | 26 | |
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| 1.5121 | 1.5133 | 27 | |
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| 1.4869 | 1.4217 | 28 | |
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| 1.4539 | 1.5602 | 29 | |
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| 1.4650 | 1.4699 | 30 | |
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| 1.4508 | 1.4319 | 31 | |
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| 1.3910 | 1.5975 | 32 | |
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| 1.3758 | 1.4031 | 33 | |
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| 1.3550 | 1.4295 | 34 | |
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| 1.3405 | 1.3804 | 35 | |
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| 1.3144 | 1.4202 | 36 | |
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| 1.3136 | 1.5135 | 37 | |
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| 1.2617 | 1.4790 | 38 | |
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| 1.2260 | 1.4108 | 39 | |
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| 1.2348 | 1.3108 | 40 | |
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| 1.2019 | 1.1461 | 41 | |
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| 1.1775 | 1.2509 | 42 | |
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| 1.1690 | 1.2179 | 43 | |
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| 1.1318 | 1.2483 | 44 | |
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| 1.1013 | 1.0815 | 45 | |
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| 1.0735 | 1.2135 | 46 | |
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| 1.0439 | 1.1260 | 47 | |
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| 1.0182 | 1.1993 | 48 | |
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| 0.9971 | 1.0797 | 49 | |
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| 0.9583 | 1.2587 | 50 | |
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| 0.9505 | 1.0793 | 51 | |
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| 0.9366 | 1.0501 | 52 | |
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| 0.9170 | 1.1476 | 53 | |
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| 0.8741 | 1.0560 | 54 | |
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| 0.8558 | 1.0024 | 55 | |
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| 0.8394 | 0.9604 | 56 | |
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| 0.8203 | 1.2700 | 57 | |
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| 0.7938 | 1.1081 | 58 | |
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| 0.7800 | 1.0198 | 59 | |
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| 0.7378 | 1.1748 | 60 | |
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| 0.7119 | 1.1299 | 61 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- TensorFlow 2.8.0 |
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- Datasets 2.2.0 |
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- Tokenizers 0.12.1 |
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