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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: pijarcandra22/t5Indo2Jawa |
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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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# pijarcandra22/t5Indo2Jawa |
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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: 1.6101 |
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- Validation Loss: 1.5534 |
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- Epoch: 130 |
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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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| 3.5149 | 3.1567 | 0 | |
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| 3.3816 | 3.0397 | 1 | |
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| 3.2812 | 2.9518 | 2 | |
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| 3.1977 | 2.8751 | 3 | |
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| 3.1223 | 2.8078 | 4 | |
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| 3.0599 | 2.7507 | 5 | |
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| 3.0019 | 2.6979 | 6 | |
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| 2.9517 | 2.6513 | 7 | |
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| 2.9034 | 2.6121 | 8 | |
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| 2.8638 | 2.5756 | 9 | |
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| 2.8232 | 2.5391 | 10 | |
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| 2.7856 | 2.5089 | 11 | |
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| 2.7541 | 2.4786 | 12 | |
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| 2.7219 | 2.4499 | 13 | |
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| 2.6935 | 2.4256 | 14 | |
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| 2.6658 | 2.4010 | 15 | |
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| 2.6389 | 2.3762 | 16 | |
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| 2.6143 | 2.3550 | 17 | |
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| 2.5899 | 2.3313 | 18 | |
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| 2.5665 | 2.3156 | 19 | |
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| 2.5445 | 2.2939 | 20 | |
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| 2.5224 | 2.2750 | 21 | |
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| 2.5022 | 2.2569 | 22 | |
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| 2.4834 | 2.2410 | 23 | |
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| 2.4641 | 2.2220 | 24 | |
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| 2.4443 | 2.2091 | 25 | |
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| 2.4267 | 2.1948 | 26 | |
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| 2.4129 | 2.1796 | 27 | |
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| 2.3937 | 2.1657 | 28 | |
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| 2.3782 | 2.1523 | 29 | |
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| 2.3616 | 2.1385 | 30 | |
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| 2.3471 | 2.1267 | 31 | |
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| 2.3351 | 2.1110 | 32 | |
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| 2.3184 | 2.0988 | 33 | |
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| 2.3047 | 2.0871 | 34 | |
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| 2.2920 | 2.0768 | 35 | |
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| 2.2767 | 2.0649 | 36 | |
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| 2.2651 | 2.0546 | 37 | |
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| 2.2526 | 2.0445 | 38 | |
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| 2.2388 | 2.0333 | 39 | |
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| 2.2264 | 2.0234 | 40 | |
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| 2.2157 | 2.0165 | 41 | |
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| 2.2050 | 2.0049 | 42 | |
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| 2.1906 | 1.9946 | 43 | |
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| 2.1824 | 1.9845 | 44 | |
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| 2.1673 | 1.9762 | 45 | |
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| 2.1559 | 1.9679 | 46 | |
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| 2.1455 | 1.9608 | 47 | |
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| 2.1377 | 1.9528 | 48 | |
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| 2.1279 | 1.9429 | 49 | |
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| 2.1176 | 1.9356 | 50 | |
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| 2.1056 | 1.9267 | 51 | |
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| 2.0979 | 1.9174 | 52 | |
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| 2.0882 | 1.9087 | 53 | |
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| 2.0802 | 1.8995 | 54 | |
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| 2.0668 | 1.8947 | 55 | |
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| 2.0597 | 1.8880 | 56 | |
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| 2.0484 | 1.8779 | 57 | |
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| 2.0405 | 1.8735 | 58 | |
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| 2.0335 | 1.8676 | 59 | |
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| 2.0254 | 1.8603 | 60 | |
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| 2.0147 | 1.8530 | 61 | |
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| 2.0078 | 1.8459 | 62 | |
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| 1.9984 | 1.8403 | 63 | |
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| 1.9902 | 1.8338 | 64 | |
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| 1.9824 | 1.8264 | 65 | |
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| 1.9768 | 1.8231 | 66 | |
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| 1.9679 | 1.8158 | 67 | |
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| 1.9597 | 1.8104 | 68 | |
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| 1.9531 | 1.8026 | 69 | |
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| 1.9460 | 1.7987 | 70 | |
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| 1.9416 | 1.7929 | 71 | |
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| 1.9291 | 1.7876 | 72 | |
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| 1.9245 | 1.7807 | 73 | |
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| 1.9143 | 1.7788 | 74 | |
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| 1.9088 | 1.7717 | 75 | |
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| 1.9006 | 1.7643 | 76 | |
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| 1.8960 | 1.7587 | 77 | |
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| 1.8901 | 1.7528 | 78 | |
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| 1.8808 | 1.7477 | 79 | |
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| 1.8740 | 1.7436 | 80 | |
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| 1.8689 | 1.7376 | 81 | |
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| 1.8628 | 1.7320 | 82 | |
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| 1.8533 | 1.7312 | 83 | |
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| 1.8486 | 1.7240 | 84 | |
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| 1.8428 | 1.7186 | 85 | |
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| 1.8351 | 1.7141 | 86 | |
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| 1.8316 | 1.7106 | 87 | |
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| 1.8234 | 1.7045 | 88 | |
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| 1.8173 | 1.6976 | 89 | |
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| 1.8109 | 1.6959 | 90 | |
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| 1.8059 | 1.6924 | 91 | |
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| 1.8016 | 1.6860 | 92 | |
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| 1.7922 | 1.6802 | 93 | |
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| 1.7887 | 1.6778 | 94 | |
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| 1.7832 | 1.6716 | 95 | |
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| 1.7761 | 1.6688 | 96 | |
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| 1.7724 | 1.6653 | 97 | |
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| 1.7662 | 1.6582 | 98 | |
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| 1.7607 | 1.6571 | 99 | |
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| 1.7549 | 1.6542 | 100 | |
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| 1.7483 | 1.6497 | 101 | |
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| 1.7454 | 1.6435 | 102 | |
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| 1.7400 | 1.6407 | 103 | |
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| 1.7318 | 1.6363 | 104 | |
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| 1.7266 | 1.6327 | 105 | |
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| 1.7234 | 1.6286 | 106 | |
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| 1.7210 | 1.6267 | 107 | |
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| 1.7109 | 1.6207 | 108 | |
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| 1.7079 | 1.6183 | 109 | |
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| 1.7026 | 1.6162 | 110 | |
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| 1.6989 | 1.6137 | 111 | |
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| 1.6925 | 1.6074 | 112 | |
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| 1.6880 | 1.6051 | 113 | |
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| 1.6823 | 1.6021 | 114 | |
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| 1.6780 | 1.5969 | 115 | |
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| 1.6737 | 1.5960 | 116 | |
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| 1.6659 | 1.5937 | 117 | |
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| 1.6603 | 1.5872 | 118 | |
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| 1.6586 | 1.5870 | 119 | |
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| 1.6550 | 1.5813 | 120 | |
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| 1.6506 | 1.5788 | 121 | |
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| 1.6432 | 1.5771 | 122 | |
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| 1.6408 | 1.5721 | 123 | |
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| 1.6377 | 1.5729 | 124 | |
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| 1.6307 | 1.5693 | 125 | |
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| 1.6268 | 1.5650 | 126 | |
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| 1.6227 | 1.5607 | 127 | |
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| 1.6180 | 1.5618 | 128 | |
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| 1.6151 | 1.5590 | 129 | |
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| 1.6101 | 1.5534 | 130 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.14.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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