--- license: apache-2.0 base_model: t5-small tags: - generated_from_keras_callback model-index: - name: pijarcandra22/t5Indo2Bali results: [] --- # pijarcandra22/t5Indo2Bali 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: 1.1220 - Validation Loss: 1.5704 - Epoch: 196 ## 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 | |:----------:|:---------------:|:-----:| | 1.8126 | 1.8072 | 0 | | 1.8017 | 1.8049 | 1 | | 1.7984 | 1.8042 | 2 | | 1.7845 | 1.7983 | 3 | | 1.7843 | 1.7968 | 4 | | 1.7812 | 1.7930 | 5 | | 1.7593 | 1.7946 | 6 | | 1.7647 | 1.7865 | 7 | | 1.7710 | 1.7826 | 8 | | 1.7464 | 1.7852 | 9 | | 1.7467 | 1.7751 | 10 | | 1.7380 | 1.7758 | 11 | | 1.7417 | 1.7761 | 12 | | 1.7433 | 1.7652 | 13 | | 1.7306 | 1.7678 | 14 | | 1.7226 | 1.7649 | 15 | | 1.7102 | 1.7608 | 16 | | 1.7125 | 1.7589 | 17 | | 1.7005 | 1.7572 | 18 | | 1.6927 | 1.7522 | 19 | | 1.6859 | 1.7467 | 20 | | 1.6895 | 1.7454 | 21 | | 1.6780 | 1.7415 | 22 | | 1.6807 | 1.7408 | 23 | | 1.6730 | 1.7376 | 24 | | 1.6673 | 1.7353 | 25 | | 1.6648 | 1.7340 | 26 | | 1.6566 | 1.7328 | 27 | | 1.6537 | 1.7278 | 28 | | 1.6508 | 1.7304 | 29 | | 1.6445 | 1.7267 | 30 | | 1.6437 | 1.7268 | 31 | | 1.6345 | 1.7249 | 32 | | 1.6228 | 1.7192 | 33 | | 1.6310 | 1.7136 | 34 | | 1.6236 | 1.7140 | 35 | | 1.6151 | 1.7158 | 36 | | 1.6114 | 1.7107 | 37 | | 1.6076 | 1.7115 | 38 | | 1.6047 | 1.7066 | 39 | | 1.5923 | 1.7089 | 40 | | 1.5897 | 1.7024 | 41 | | 1.5822 | 1.7000 | 42 | | 1.5815 | 1.6983 | 43 | | 1.5854 | 1.6984 | 44 | | 1.5728 | 1.6962 | 45 | | 1.5672 | 1.6971 | 46 | | 1.5735 | 1.6899 | 47 | | 1.5576 | 1.6894 | 48 | | 1.5649 | 1.6853 | 49 | | 1.5572 | 1.6839 | 50 | | 1.5534 | 1.6813 | 51 | | 1.5491 | 1.6811 | 52 | | 1.5487 | 1.6807 | 53 | | 1.5376 | 1.6763 | 54 | | 1.5367 | 1.6772 | 55 | | 1.5242 | 1.6744 | 56 | | 1.5251 | 1.6687 | 57 | | 1.5246 | 1.6708 | 58 | | 1.5260 | 1.6673 | 59 | | 1.5073 | 1.6699 | 60 | | 1.5063 | 1.6658 | 61 | | 1.5238 | 1.6630 | 62 | | 1.4991 | 1.6612 | 63 | | 1.4994 | 1.6610 | 64 | | 1.5001 | 1.6599 | 65 | | 1.4911 | 1.6612 | 66 | | 1.4926 | 1.6554 | 67 | | 1.4852 | 1.6527 | 68 | | 1.4720 | 1.6554 | 69 | | 1.4740 | 1.6533 | 70 | | 1.4759 | 1.6487 | 71 | | 1.4692 | 1.6450 | 72 | | 1.4632 | 1.6480 | 73 | | 1.4664 | 1.6424 | 74 | | 1.4591 | 1.6436 | 75 | | 1.4606 | 1.6384 | 76 | | 1.4487 | 1.6382 | 77 | | 1.4558 | 1.6375 | 78 | | 1.4455 | 1.6389 | 79 | | 1.4396 | 1.6427 | 80 | | 1.4441 | 1.6363 | 81 | | 1.4333 | 1.6357 | 82 | | 1.4414 | 1.6348 | 83 | | 1.4260 | 1.6319 | 84 | | 1.4249 | 1.6317 | 85 | | 1.4166 | 1.6268 | 86 | | 1.4167 | 1.6301 | 87 | | 1.4150 | 1.6244 | 88 | | 1.4061 | 1.6273 | 89 | | 1.4134 | 1.6260 | 90 | | 1.4022 | 1.6237 | 91 | | 1.3949 | 1.6246 | 92 | | 1.4007 | 1.6231 | 93 | | 1.3987 | 1.6184 | 94 | | 1.3919 | 1.6178 | 95 | | 1.3889 | 1.6178 | 96 | | 1.3883 | 1.6209 | 97 | | 1.3756 | 1.6175 | 98 | | 1.3818 | 1.6139 | 99 | | 1.3772 | 1.6129 | 100 | | 1.3726 | 1.6159 | 101 | | 1.3695 | 1.6158 | 102 | | 1.3707 | 1.6110 | 103 | | 1.3555 | 1.6132 | 104 | | 1.3592 | 1.6085 | 105 | | 1.3562 | 1.6111 | 106 | | 1.3475 | 1.6095 | 107 | | 1.3460 | 1.6100 | 108 | | 1.3446 | 1.6093 | 109 | | 1.3436 | 1.6095 | 110 | | 1.3452 | 1.6068 | 111 | | 1.3401 | 1.6054 | 112 | | 1.3378 | 1.6085 | 113 | | 1.3288 | 1.6056 | 114 | | 1.3294 | 1.6057 | 115 | | 1.3227 | 1.6018 | 116 | | 1.3270 | 1.5989 | 117 | | 1.3214 | 1.5956 | 118 | | 1.3187 | 1.5986 | 119 | | 1.3150 | 1.5986 | 120 | | 1.3145 | 1.5958 | 121 | | 1.3159 | 1.5980 | 122 | | 1.3050 | 1.5978 | 123 | | 1.3113 | 1.5956 | 124 | | 1.2932 | 1.5972 | 125 | | 1.3008 | 1.5927 | 126 | | 1.2963 | 1.5960 | 127 | | 1.2799 | 1.5950 | 128 | | 1.2879 | 1.5918 | 129 | | 1.2873 | 1.5891 | 130 | | 1.2868 | 1.5884 | 131 | | 1.2789 | 1.5922 | 132 | | 1.2751 | 1.5887 | 133 | | 1.2780 | 1.5888 | 134 | | 1.2632 | 1.5913 | 135 | | 1.2617 | 1.5835 | 136 | | 1.2681 | 1.5910 | 137 | | 1.2630 | 1.5893 | 138 | | 1.2631 | 1.5877 | 139 | | 1.2540 | 1.5892 | 140 | | 1.2518 | 1.5812 | 141 | | 1.2611 | 1.5812 | 142 | | 1.2561 | 1.5808 | 143 | | 1.2483 | 1.5757 | 144 | | 1.2424 | 1.5785 | 145 | | 1.2366 | 1.5806 | 146 | | 1.2393 | 1.5801 | 147 | | 1.2359 | 1.5781 | 148 | | 1.2256 | 1.5796 | 149 | | 1.2261 | 1.5818 | 150 | | 1.2179 | 1.5782 | 151 | | 1.2321 | 1.5720 | 152 | | 1.2198 | 1.5744 | 153 | | 1.2189 | 1.5780 | 154 | | 1.2301 | 1.5747 | 155 | | 1.2131 | 1.5776 | 156 | | 1.2095 | 1.5746 | 157 | | 1.2134 | 1.5756 | 158 | | 1.2061 | 1.5761 | 159 | | 1.2068 | 1.5727 | 160 | | 1.2061 | 1.5714 | 161 | | 1.1998 | 1.5756 | 162 | | 1.1967 | 1.5780 | 163 | | 1.1940 | 1.5747 | 164 | | 1.1869 | 1.5713 | 165 | | 1.1980 | 1.5700 | 166 | | 1.1958 | 1.5714 | 167 | | 1.1867 | 1.5666 | 168 | | 1.1779 | 1.5715 | 169 | | 1.1789 | 1.5765 | 170 | | 1.1763 | 1.5742 | 171 | | 1.1767 | 1.5708 | 172 | | 1.1840 | 1.5682 | 173 | | 1.1688 | 1.5747 | 174 | | 1.1701 | 1.5696 | 175 | | 1.1739 | 1.5658 | 176 | | 1.1572 | 1.5688 | 177 | | 1.1593 | 1.5659 | 178 | | 1.1591 | 1.5684 | 179 | | 1.1581 | 1.5644 | 180 | | 1.1635 | 1.5655 | 181 | | 1.1538 | 1.5662 | 182 | | 1.1455 | 1.5666 | 183 | | 1.1442 | 1.5650 | 184 | | 1.1398 | 1.5668 | 185 | | 1.1408 | 1.5712 | 186 | | 1.1364 | 1.5679 | 187 | | 1.1348 | 1.5653 | 188 | | 1.1358 | 1.5704 | 189 | | 1.1355 | 1.5652 | 190 | | 1.1278 | 1.5650 | 191 | | 1.1260 | 1.5697 | 192 | | 1.1257 | 1.5686 | 193 | | 1.1265 | 1.5712 | 194 | | 1.1248 | 1.5625 | 195 | | 1.1220 | 1.5704 | 196 | ### Framework versions - Transformers 4.35.2 - TensorFlow 2.14.0 - Datasets 2.15.0 - Tokenizers 0.15.0