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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_keras_callback
model-index:
- name: pijarcandra22/t5Indo2Jawa
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# pijarcandra22/t5Indo2Jawa
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.3740
- Validation Loss: 1.4176
- Epoch: 199
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- 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}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.5149 | 3.1567 | 0 |
| 3.3816 | 3.0397 | 1 |
| 3.2812 | 2.9518 | 2 |
| 3.1977 | 2.8751 | 3 |
| 3.1223 | 2.8078 | 4 |
| 3.0599 | 2.7507 | 5 |
| 3.0019 | 2.6979 | 6 |
| 2.9517 | 2.6513 | 7 |
| 2.9034 | 2.6121 | 8 |
| 2.8638 | 2.5756 | 9 |
| 2.8232 | 2.5391 | 10 |
| 2.7856 | 2.5089 | 11 |
| 2.7541 | 2.4786 | 12 |
| 2.7219 | 2.4499 | 13 |
| 2.6935 | 2.4256 | 14 |
| 2.6658 | 2.4010 | 15 |
| 2.6389 | 2.3762 | 16 |
| 2.6143 | 2.3550 | 17 |
| 2.5899 | 2.3313 | 18 |
| 2.5665 | 2.3156 | 19 |
| 2.5445 | 2.2939 | 20 |
| 2.5224 | 2.2750 | 21 |
| 2.5022 | 2.2569 | 22 |
| 2.4834 | 2.2410 | 23 |
| 2.4641 | 2.2220 | 24 |
| 2.4443 | 2.2091 | 25 |
| 2.4267 | 2.1948 | 26 |
| 2.4129 | 2.1796 | 27 |
| 2.3937 | 2.1657 | 28 |
| 2.3782 | 2.1523 | 29 |
| 2.3616 | 2.1385 | 30 |
| 2.3471 | 2.1267 | 31 |
| 2.3351 | 2.1110 | 32 |
| 2.3184 | 2.0988 | 33 |
| 2.3047 | 2.0871 | 34 |
| 2.2920 | 2.0768 | 35 |
| 2.2767 | 2.0649 | 36 |
| 2.2651 | 2.0546 | 37 |
| 2.2526 | 2.0445 | 38 |
| 2.2388 | 2.0333 | 39 |
| 2.2264 | 2.0234 | 40 |
| 2.2157 | 2.0165 | 41 |
| 2.2050 | 2.0049 | 42 |
| 2.1906 | 1.9946 | 43 |
| 2.1824 | 1.9845 | 44 |
| 2.1673 | 1.9762 | 45 |
| 2.1559 | 1.9679 | 46 |
| 2.1455 | 1.9608 | 47 |
| 2.1377 | 1.9528 | 48 |
| 2.1279 | 1.9429 | 49 |
| 2.1176 | 1.9356 | 50 |
| 2.1056 | 1.9267 | 51 |
| 2.0979 | 1.9174 | 52 |
| 2.0882 | 1.9087 | 53 |
| 2.0802 | 1.8995 | 54 |
| 2.0668 | 1.8947 | 55 |
| 2.0597 | 1.8880 | 56 |
| 2.0484 | 1.8779 | 57 |
| 2.0405 | 1.8735 | 58 |
| 2.0335 | 1.8676 | 59 |
| 2.0254 | 1.8603 | 60 |
| 2.0147 | 1.8530 | 61 |
| 2.0078 | 1.8459 | 62 |
| 1.9984 | 1.8403 | 63 |
| 1.9902 | 1.8338 | 64 |
| 1.9824 | 1.8264 | 65 |
| 1.9768 | 1.8231 | 66 |
| 1.9679 | 1.8158 | 67 |
| 1.9597 | 1.8104 | 68 |
| 1.9531 | 1.8026 | 69 |
| 1.9460 | 1.7987 | 70 |
| 1.9416 | 1.7929 | 71 |
| 1.9291 | 1.7876 | 72 |
| 1.9245 | 1.7807 | 73 |
| 1.9143 | 1.7788 | 74 |
| 1.9088 | 1.7717 | 75 |
| 1.9006 | 1.7643 | 76 |
| 1.8960 | 1.7587 | 77 |
| 1.8901 | 1.7528 | 78 |
| 1.8808 | 1.7477 | 79 |
| 1.8740 | 1.7436 | 80 |
| 1.8689 | 1.7376 | 81 |
| 1.8628 | 1.7320 | 82 |
| 1.8533 | 1.7312 | 83 |
| 1.8486 | 1.7240 | 84 |
| 1.8428 | 1.7186 | 85 |
| 1.8351 | 1.7141 | 86 |
| 1.8316 | 1.7106 | 87 |
| 1.8234 | 1.7045 | 88 |
| 1.8173 | 1.6976 | 89 |
| 1.8109 | 1.6959 | 90 |
| 1.8059 | 1.6924 | 91 |
| 1.8016 | 1.6860 | 92 |
| 1.7922 | 1.6802 | 93 |
| 1.7887 | 1.6778 | 94 |
| 1.7832 | 1.6716 | 95 |
| 1.7761 | 1.6688 | 96 |
| 1.7724 | 1.6653 | 97 |
| 1.7662 | 1.6582 | 98 |
| 1.7607 | 1.6571 | 99 |
| 1.7549 | 1.6542 | 100 |
| 1.7483 | 1.6497 | 101 |
| 1.7454 | 1.6435 | 102 |
| 1.7400 | 1.6407 | 103 |
| 1.7318 | 1.6363 | 104 |
| 1.7266 | 1.6327 | 105 |
| 1.7234 | 1.6286 | 106 |
| 1.7210 | 1.6267 | 107 |
| 1.7109 | 1.6207 | 108 |
| 1.7079 | 1.6183 | 109 |
| 1.7026 | 1.6162 | 110 |
| 1.6989 | 1.6137 | 111 |
| 1.6925 | 1.6074 | 112 |
| 1.6880 | 1.6051 | 113 |
| 1.6823 | 1.6021 | 114 |
| 1.6780 | 1.5969 | 115 |
| 1.6737 | 1.5960 | 116 |
| 1.6659 | 1.5937 | 117 |
| 1.6603 | 1.5872 | 118 |
| 1.6586 | 1.5870 | 119 |
| 1.6550 | 1.5813 | 120 |
| 1.6506 | 1.5788 | 121 |
| 1.6432 | 1.5771 | 122 |
| 1.6408 | 1.5721 | 123 |
| 1.6377 | 1.5729 | 124 |
| 1.6307 | 1.5693 | 125 |
| 1.6268 | 1.5650 | 126 |
| 1.6227 | 1.5607 | 127 |
| 1.6180 | 1.5618 | 128 |
| 1.6151 | 1.5590 | 129 |
| 1.6101 | 1.5534 | 130 |
| 1.6056 | 1.5505 | 131 |
| 1.6034 | 1.5470 | 132 |
| 1.5971 | 1.5443 | 133 |
| 1.5926 | 1.5431 | 134 |
| 1.5873 | 1.5421 | 135 |
| 1.5850 | 1.5378 | 136 |
| 1.5807 | 1.5334 | 137 |
| 1.5771 | 1.5335 | 138 |
| 1.5734 | 1.5309 | 139 |
| 1.5694 | 1.5288 | 140 |
| 1.5642 | 1.5273 | 141 |
| 1.5610 | 1.5215 | 142 |
| 1.5568 | 1.5217 | 143 |
| 1.5555 | 1.5171 | 144 |
| 1.5517 | 1.5170 | 145 |
| 1.5471 | 1.5148 | 146 |
| 1.5426 | 1.5120 | 147 |
| 1.5376 | 1.5102 | 148 |
| 1.5370 | 1.5081 | 149 |
| 1.5317 | 1.5070 | 150 |
| 1.5272 | 1.5029 | 151 |
| 1.5257 | 1.5025 | 152 |
| 1.5205 | 1.4997 | 153 |
| 1.5180 | 1.4954 | 154 |
| 1.5112 | 1.4932 | 155 |
| 1.5117 | 1.4920 | 156 |
| 1.5070 | 1.4890 | 157 |
| 1.5050 | 1.4881 | 158 |
| 1.4984 | 1.4870 | 159 |
| 1.4964 | 1.4843 | 160 |
| 1.4920 | 1.4833 | 161 |
| 1.4879 | 1.4808 | 162 |
| 1.4838 | 1.4768 | 163 |
| 1.4854 | 1.4756 | 164 |
| 1.4784 | 1.4733 | 165 |
| 1.4757 | 1.4724 | 166 |
| 1.4733 | 1.4697 | 167 |
| 1.4704 | 1.4678 | 168 |
| 1.4660 | 1.4648 | 169 |
| 1.4618 | 1.4660 | 170 |
| 1.4591 | 1.4606 | 171 |
| 1.4554 | 1.4626 | 172 |
| 1.4533 | 1.4595 | 173 |
| 1.4492 | 1.4583 | 174 |
| 1.4471 | 1.4539 | 175 |
| 1.4410 | 1.4548 | 176 |
| 1.4387 | 1.4507 | 177 |
| 1.4370 | 1.4484 | 178 |
| 1.4336 | 1.4482 | 179 |
| 1.4301 | 1.4468 | 180 |
| 1.4300 | 1.4441 | 181 |
| 1.4246 | 1.4429 | 182 |
| 1.4221 | 1.4440 | 183 |
| 1.4171 | 1.4418 | 184 |
| 1.4150 | 1.4359 | 185 |
| 1.4131 | 1.4377 | 186 |
| 1.4110 | 1.4358 | 187 |
| 1.4081 | 1.4321 | 188 |
| 1.4025 | 1.4333 | 189 |
| 1.4010 | 1.4293 | 190 |
| 1.3966 | 1.4288 | 191 |
| 1.3949 | 1.4293 | 192 |
| 1.3921 | 1.4252 | 193 |
| 1.3914 | 1.4253 | 194 |
| 1.3866 | 1.4240 | 195 |
| 1.3832 | 1.4208 | 196 |
| 1.3818 | 1.4221 | 197 |
| 1.3765 | 1.4185 | 198 |
| 1.3740 | 1.4176 | 199 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0
|