metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_keras_callback
model-index:
- name: pijarcandra22/NMTIndoBaliT5
results: []
pijarcandra22/NMTIndoBaliT5
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1252
- Validation Loss: 2.2681
- Epoch: 229
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': 1e-04, '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 |
---|---|---|
3.2881 | 2.6852 | 0 |
2.7514 | 2.4004 | 1 |
2.5012 | 2.2171 | 2 |
2.3252 | 2.0959 | 3 |
2.1930 | 1.9901 | 4 |
2.0837 | 1.9130 | 5 |
1.9912 | 1.8452 | 6 |
1.9107 | 1.7974 | 7 |
1.8459 | 1.7521 | 8 |
1.7902 | 1.7165 | 9 |
1.7321 | 1.6842 | 10 |
1.6811 | 1.6400 | 11 |
1.6374 | 1.6230 | 12 |
1.5973 | 1.5960 | 13 |
1.5588 | 1.5765 | 14 |
1.5244 | 1.5589 | 15 |
1.4933 | 1.5370 | 16 |
1.4588 | 1.5300 | 17 |
1.4325 | 1.5107 | 18 |
1.4054 | 1.4970 | 19 |
1.3730 | 1.4839 | 20 |
1.3475 | 1.4789 | 21 |
1.3231 | 1.4616 | 22 |
1.3035 | 1.4568 | 23 |
1.2768 | 1.4489 | 24 |
1.2587 | 1.4396 | 25 |
1.2380 | 1.4364 | 26 |
1.2208 | 1.4273 | 27 |
1.2026 | 1.4228 | 28 |
1.1755 | 1.4141 | 29 |
1.1614 | 1.4062 | 30 |
1.1460 | 1.4060 | 31 |
1.1289 | 1.3934 | 32 |
1.1134 | 1.4007 | 33 |
1.0965 | 1.3927 | 34 |
1.0818 | 1.3874 | 35 |
1.0661 | 1.3921 | 36 |
1.0482 | 1.3795 | 37 |
1.0345 | 1.3853 | 38 |
1.0195 | 1.3835 | 39 |
1.0074 | 1.3772 | 40 |
0.9890 | 1.3851 | 41 |
0.9833 | 1.3724 | 42 |
0.9667 | 1.3740 | 43 |
0.9561 | 1.3752 | 44 |
0.9429 | 1.3673 | 45 |
0.9301 | 1.3828 | 46 |
0.9141 | 1.3806 | 47 |
0.9050 | 1.3772 | 48 |
0.8952 | 1.3812 | 49 |
0.8809 | 1.3718 | 50 |
0.8725 | 1.3825 | 51 |
0.8601 | 1.3842 | 52 |
0.8488 | 1.3827 | 53 |
0.8375 | 1.3920 | 54 |
0.8257 | 1.3936 | 55 |
0.8184 | 1.3842 | 56 |
0.8081 | 1.3846 | 57 |
0.7986 | 1.3860 | 58 |
0.7883 | 1.3943 | 59 |
0.7787 | 1.4004 | 60 |
0.7666 | 1.4071 | 61 |
0.7554 | 1.4079 | 62 |
0.7470 | 1.4038 | 63 |
0.7366 | 1.4141 | 64 |
0.7279 | 1.4135 | 65 |
0.7250 | 1.4111 | 66 |
0.7128 | 1.4196 | 67 |
0.7042 | 1.4182 | 68 |
0.6946 | 1.4378 | 69 |
0.6851 | 1.4350 | 70 |
0.6764 | 1.4403 | 71 |
0.6695 | 1.4474 | 72 |
0.6606 | 1.4454 | 73 |
0.6565 | 1.4516 | 74 |
0.6450 | 1.4595 | 75 |
0.6347 | 1.4700 | 76 |
0.6287 | 1.4746 | 77 |
0.6183 | 1.4813 | 78 |
0.6143 | 1.4785 | 79 |
0.6053 | 1.4848 | 80 |
0.5994 | 1.4777 | 81 |
0.5903 | 1.4962 | 82 |
0.5828 | 1.5102 | 83 |
0.5760 | 1.4957 | 84 |
0.5696 | 1.5121 | 85 |
0.5637 | 1.5168 | 86 |
0.5578 | 1.5183 | 87 |
0.5499 | 1.5184 | 88 |
0.5396 | 1.5433 | 89 |
0.5345 | 1.5411 | 90 |
0.5268 | 1.5338 | 91 |
0.5220 | 1.5556 | 92 |
0.5184 | 1.5489 | 93 |
0.5122 | 1.5635 | 94 |
0.5014 | 1.5674 | 95 |
0.4921 | 1.5773 | 96 |
0.4925 | 1.5773 | 97 |
0.4821 | 1.5938 | 98 |
0.4769 | 1.6013 | 99 |
0.4723 | 1.5979 | 100 |
0.4692 | 1.6131 | 101 |
0.4603 | 1.6247 | 102 |
0.4553 | 1.6276 | 103 |
0.4476 | 1.6376 | 104 |
0.4401 | 1.6390 | 105 |
0.4384 | 1.6442 | 106 |
0.4305 | 1.6548 | 107 |
0.4263 | 1.6617 | 108 |
0.4232 | 1.6523 | 109 |
0.4185 | 1.6561 | 110 |
0.4129 | 1.6779 | 111 |
0.4036 | 1.6897 | 112 |
0.4005 | 1.6873 | 113 |
0.3948 | 1.6987 | 114 |
0.3892 | 1.7120 | 115 |
0.3859 | 1.7049 | 116 |
0.3795 | 1.7241 | 117 |
0.3802 | 1.7273 | 118 |
0.3731 | 1.7387 | 119 |
0.3672 | 1.7447 | 120 |
0.3629 | 1.7513 | 121 |
0.3607 | 1.7515 | 122 |
0.3543 | 1.7585 | 123 |
0.3504 | 1.7601 | 124 |
0.3477 | 1.7657 | 125 |
0.3453 | 1.7733 | 126 |
0.3448 | 1.7718 | 127 |
0.3390 | 1.7971 | 128 |
0.3352 | 1.7929 | 129 |
0.3273 | 1.7988 | 130 |
0.3250 | 1.8192 | 131 |
0.3222 | 1.8220 | 132 |
0.3173 | 1.8289 | 133 |
0.3171 | 1.8261 | 134 |
0.3124 | 1.8415 | 135 |
0.3040 | 1.8379 | 136 |
0.3040 | 1.8533 | 137 |
0.3030 | 1.8511 | 138 |
0.2970 | 1.8537 | 139 |
0.2938 | 1.8697 | 140 |
0.2929 | 1.8730 | 141 |
0.2892 | 1.8632 | 142 |
0.2816 | 1.8796 | 143 |
0.2812 | 1.8870 | 144 |
0.2761 | 1.8891 | 145 |
0.2731 | 1.9134 | 146 |
0.2698 | 1.9100 | 147 |
0.2671 | 1.9207 | 148 |
0.2639 | 1.9196 | 149 |
0.2621 | 1.9130 | 150 |
0.2589 | 1.9273 | 151 |
0.2558 | 1.9336 | 152 |
0.2545 | 1.9355 | 153 |
0.2487 | 1.9551 | 154 |
0.2493 | 1.9573 | 155 |
0.2449 | 1.9552 | 156 |
0.2421 | 1.9591 | 157 |
0.2405 | 1.9556 | 158 |
0.2367 | 1.9807 | 159 |
0.2342 | 1.9859 | 160 |
0.2316 | 1.9803 | 161 |
0.2281 | 1.9853 | 162 |
0.2269 | 1.9970 | 163 |
0.2250 | 2.0120 | 164 |
0.2236 | 2.0107 | 165 |
0.2194 | 2.0208 | 166 |
0.2183 | 2.0198 | 167 |
0.2168 | 2.0265 | 168 |
0.2172 | 2.0278 | 169 |
0.2117 | 2.0380 | 170 |
0.2078 | 2.0448 | 171 |
0.2091 | 2.0415 | 172 |
0.2065 | 2.0459 | 173 |
0.2027 | 2.0597 | 174 |
0.1995 | 2.0659 | 175 |
0.1980 | 2.0811 | 176 |
0.1971 | 2.0704 | 177 |
0.1932 | 2.0785 | 178 |
0.1892 | 2.0783 | 179 |
0.1924 | 2.0742 | 180 |
0.1872 | 2.0979 | 181 |
0.1858 | 2.0958 | 182 |
0.1853 | 2.1005 | 183 |
0.1834 | 2.1166 | 184 |
0.1810 | 2.1027 | 185 |
0.1789 | 2.1151 | 186 |
0.1768 | 2.1302 | 187 |
0.1768 | 2.1200 | 188 |
0.1766 | 2.1399 | 189 |
0.1732 | 2.1196 | 190 |
0.1719 | 2.1362 | 191 |
0.1697 | 2.1447 | 192 |
0.1684 | 2.1464 | 193 |
0.1699 | 2.1442 | 194 |
0.1657 | 2.1492 | 195 |
0.1607 | 2.1644 | 196 |
0.1603 | 2.1667 | 197 |
0.1580 | 2.1715 | 198 |
0.1588 | 2.1818 | 199 |
0.1551 | 2.1825 | 200 |
0.1572 | 2.1779 | 201 |
0.1552 | 2.1842 | 202 |
0.1528 | 2.2038 | 203 |
0.1530 | 2.1941 | 204 |
0.1501 | 2.1903 | 205 |
0.1492 | 2.2089 | 206 |
0.1498 | 2.1871 | 207 |
0.1481 | 2.1888 | 208 |
0.1486 | 2.2130 | 209 |
0.1434 | 2.2259 | 210 |
0.1432 | 2.2159 | 211 |
0.1436 | 2.2151 | 212 |
0.1411 | 2.2221 | 213 |
0.1414 | 2.2294 | 214 |
0.1381 | 2.2310 | 215 |
0.1360 | 2.2444 | 216 |
0.1353 | 2.2427 | 217 |
0.1372 | 2.2461 | 218 |
0.1350 | 2.2455 | 219 |
0.1319 | 2.2616 | 220 |
0.1345 | 2.2556 | 221 |
0.1319 | 2.2567 | 222 |
0.1301 | 2.2589 | 223 |
0.1273 | 2.2709 | 224 |
0.1266 | 2.2737 | 225 |
0.1251 | 2.2794 | 226 |
0.1255 | 2.2707 | 227 |
0.1264 | 2.2903 | 228 |
0.1252 | 2.2681 | 229 |
Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2