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--- |
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license: mit |
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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/gamza-bart-for-kormath128 |
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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/gamza-bart-for-kormath128 |
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This model is a fine-tuned version of [gogamza/kobart-base-v2](https://huggingface.co/gogamza/kobart-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.1429 |
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- Validation Loss: 0.3575 |
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- Epoch: 42 |
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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': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 5.9513 | 3.2241 | 0 | |
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| 2.6808 | 1.8567 | 1 | |
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| 1.6770 | 1.2966 | 2 | |
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| 1.2253 | 1.0402 | 3 | |
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| 1.0279 | 0.9159 | 4 | |
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| 0.9241 | 0.8158 | 5 | |
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| 0.8570 | 0.8047 | 6 | |
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| 0.8130 | 0.7684 | 7 | |
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| 0.7771 | 0.7817 | 8 | |
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| 0.7522 | 0.7653 | 9 | |
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| 0.7318 | 0.6813 | 10 | |
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| 0.7111 | 0.6535 | 11 | |
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| 0.6916 | 0.6719 | 12 | |
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| 0.6901 | 0.7191 | 13 | |
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| 0.6551 | 0.6330 | 14 | |
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| 0.6495 | 0.6242 | 15 | |
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| 0.6258 | 0.6048 | 16 | |
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| 0.6184 | 0.6590 | 17 | |
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| 0.6055 | 0.6622 | 18 | |
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| 0.5946 | 0.6377 | 19 | |
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| 0.5807 | 0.5994 | 20 | |
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| 0.5781 | 0.5797 | 21 | |
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| 0.5644 | 0.6154 | 22 | |
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| 0.5466 | 0.5777 | 23 | |
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| 0.5417 | 0.6324 | 24 | |
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| 0.5204 | 0.5763 | 25 | |
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| 0.5081 | 0.5751 | 26 | |
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| 0.4923 | 0.5908 | 27 | |
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| 0.4616 | 0.5433 | 28 | |
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| 0.4238 | 0.4823 | 29 | |
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| 0.3765 | 0.4474 | 30 | |
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| 0.3447 | 0.4306 | 31 | |
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| 0.3156 | 0.3817 | 32 | |
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| 0.2832 | 0.3824 | 33 | |
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| 0.2632 | 0.3204 | 34 | |
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| 0.2365 | 0.3539 | 35 | |
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| 0.2179 | 0.3162 | 36 | |
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| 0.2024 | 0.3385 | 37 | |
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| 0.1860 | 0.3367 | 38 | |
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| 0.1801 | 0.3019 | 39 | |
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| 0.1629 | 0.3045 | 40 | |
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| 0.1533 | 0.2567 | 41 | |
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| 0.1429 | 0.3575 | 42 | |
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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 2.1.0 |
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- Tokenizers 0.12.1 |
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