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--- |
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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/ke-t5-scratch |
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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/ke-t5-scratch |
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This model is a fine-tuned version of [madatnlp/ke-t5-math-py](https://huggingface.co/madatnlp/ke-t5-math-py) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.4760 |
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- Validation Loss: 0.7360 |
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- Epoch: 36 |
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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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| 4.2751 | 2.1074 | 0 | |
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| 2.2716 | 1.7945 | 1 | |
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| 1.8889 | 1.5726 | 2 | |
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| 1.6760 | 1.3722 | 3 | |
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| 1.5021 | 1.3280 | 4 | |
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| 1.4369 | 1.2523 | 5 | |
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| 1.3352 | 1.0619 | 6 | |
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| 1.2749 | 1.1156 | 7 | |
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| 1.2170 | 1.0452 | 8 | |
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| 1.1713 | 1.0596 | 9 | |
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| 1.1410 | 1.0080 | 10 | |
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| 1.0884 | 1.0213 | 11 | |
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| 1.0508 | 0.9223 | 12 | |
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| 0.9933 | 0.9353 | 13 | |
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| 0.9871 | 0.8749 | 14 | |
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| 0.9251 | 0.9173 | 15 | |
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| 0.9282 | 0.8620 | 16 | |
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| 0.8849 | 0.8093 | 17 | |
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| 0.8613 | 0.7823 | 18 | |
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| 0.8322 | 0.8016 | 19 | |
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| 0.8070 | 0.8844 | 20 | |
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| 0.7737 | 0.7635 | 21 | |
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| 0.7465 | 0.8440 | 22 | |
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| 0.7178 | 0.7958 | 23 | |
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| 0.7036 | 0.7739 | 24 | |
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| 0.6813 | 0.7347 | 25 | |
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| 0.6597 | 0.7545 | 26 | |
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| 0.6427 | 0.7394 | 27 | |
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| 0.6154 | 0.7212 | 28 | |
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| 0.5892 | 0.7653 | 29 | |
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| 0.5696 | 0.7073 | 30 | |
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| 0.5644 | 0.6977 | 31 | |
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| 0.5307 | 0.6977 | 32 | |
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| 0.5159 | 0.7736 | 33 | |
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| 0.5131 | 0.8138 | 34 | |
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| 0.4812 | 0.7623 | 35 | |
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| 0.4760 | 0.7360 | 36 | |
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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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