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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: JuliusFx/dyu-fr-t5-small_v8 |
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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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# JuliusFx/dyu-fr-t5-small_v8 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 1.9512 |
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- Validation Loss: 2.8739 |
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- Epoch: 87 |
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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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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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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| 3.1481 | 3.2663 | 0 | |
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| 3.0205 | 3.2024 | 1 | |
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| 2.9712 | 3.1559 | 2 | |
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| 2.9209 | 3.1465 | 3 | |
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| 2.8848 | 3.1125 | 4 | |
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| 2.8512 | 3.1014 | 5 | |
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| 2.8239 | 3.0771 | 6 | |
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| 2.7965 | 3.0641 | 7 | |
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| 2.7743 | 3.0431 | 8 | |
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| 2.7505 | 3.0327 | 9 | |
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| 2.7325 | 3.0072 | 10 | |
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| 2.7153 | 3.0060 | 11 | |
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| 2.6904 | 2.9950 | 12 | |
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| 2.6750 | 2.9895 | 13 | |
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| 2.6554 | 2.9700 | 14 | |
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| 2.6400 | 2.9632 | 15 | |
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| 2.6220 | 2.9534 | 16 | |
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| 2.6059 | 2.9505 | 17 | |
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| 2.5913 | 2.9536 | 18 | |
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| 2.5779 | 2.9485 | 19 | |
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| 2.5624 | 2.9349 | 20 | |
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| 2.5469 | 2.9307 | 21 | |
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| 2.5341 | 2.9224 | 22 | |
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| 2.5223 | 2.9114 | 23 | |
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| 2.5093 | 2.8996 | 24 | |
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| 2.4995 | 2.9065 | 25 | |
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| 2.4855 | 2.8974 | 26 | |
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| 2.4706 | 2.8926 | 27 | |
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| 2.4589 | 2.9075 | 28 | |
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| 2.4521 | 2.8921 | 29 | |
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| 2.4380 | 2.9055 | 30 | |
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| 2.4243 | 2.8930 | 31 | |
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| 2.4131 | 2.8871 | 32 | |
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| 2.4065 | 2.8894 | 33 | |
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| 2.3911 | 2.8890 | 34 | |
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| 2.3833 | 2.8757 | 35 | |
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| 2.3724 | 2.8778 | 36 | |
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| 2.3628 | 2.8874 | 37 | |
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| 2.3556 | 2.8687 | 38 | |
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| 2.3441 | 2.8653 | 39 | |
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| 2.3321 | 2.8794 | 40 | |
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| 2.3203 | 2.8827 | 41 | |
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| 2.3118 | 2.8778 | 42 | |
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| 2.3027 | 2.8955 | 43 | |
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| 2.2903 | 2.8778 | 44 | |
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| 2.2821 | 2.8751 | 45 | |
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| 2.2760 | 2.8655 | 46 | |
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| 2.2592 | 2.8763 | 47 | |
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| 2.2534 | 2.8643 | 48 | |
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| 2.2466 | 2.8716 | 49 | |
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| 2.2363 | 2.8728 | 50 | |
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| 2.2279 | 2.8688 | 51 | |
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| 2.2225 | 2.8822 | 52 | |
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| 2.2133 | 2.8690 | 53 | |
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| 2.2025 | 2.8551 | 54 | |
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| 2.1937 | 2.8605 | 55 | |
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| 2.1863 | 2.8441 | 56 | |
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| 2.1776 | 2.8576 | 57 | |
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| 2.1732 | 2.8435 | 58 | |
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| 2.1640 | 2.8448 | 59 | |
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| 2.1530 | 2.8422 | 60 | |
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| 2.1438 | 2.8640 | 61 | |
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| 2.1360 | 2.8648 | 62 | |
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| 2.1302 | 2.8689 | 63 | |
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| 2.1213 | 2.8787 | 64 | |
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| 2.1170 | 2.8816 | 65 | |
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| 2.1016 | 2.8655 | 66 | |
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| 2.0986 | 2.8713 | 67 | |
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| 2.0892 | 2.8776 | 68 | |
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| 2.0876 | 2.8912 | 69 | |
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| 2.0722 | 2.8901 | 70 | |
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| 2.0678 | 2.8549 | 71 | |
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| 2.0607 | 2.8883 | 72 | |
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| 2.0544 | 2.8681 | 73 | |
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| 2.0481 | 2.8637 | 74 | |
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| 2.0358 | 2.8739 | 75 | |
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| 2.0347 | 2.8705 | 76 | |
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| 2.0232 | 2.8724 | 77 | |
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| 2.0225 | 2.8619 | 78 | |
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| 2.0096 | 2.8687 | 79 | |
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| 2.0038 | 2.8561 | 80 | |
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| 1.9969 | 2.8560 | 81 | |
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| 1.9873 | 2.8755 | 82 | |
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| 1.9880 | 2.8745 | 83 | |
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| 1.9758 | 2.8648 | 84 | |
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| 1.9711 | 2.8808 | 85 | |
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| 1.9635 | 2.8721 | 86 | |
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| 1.9512 | 2.8739 | 87 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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