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: 0.0704
- Validation Loss: 2.4783
- Epoch: 342
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 |
0.1229 | 2.2939 | 230 |
0.1217 | 2.2889 | 231 |
0.1214 | 2.2855 | 232 |
0.1195 | 2.3005 | 233 |
0.1196 | 2.3030 | 234 |
0.1200 | 2.3065 | 235 |
0.1176 | 2.2957 | 236 |
0.1183 | 2.2850 | 237 |
0.1173 | 2.3067 | 238 |
0.1158 | 2.3098 | 239 |
0.1175 | 2.3070 | 240 |
0.1144 | 2.3091 | 241 |
0.1113 | 2.3286 | 242 |
0.1112 | 2.3344 | 243 |
0.1122 | 2.3201 | 244 |
0.1112 | 2.3277 | 245 |
0.1103 | 2.3282 | 246 |
0.1074 | 2.3500 | 247 |
0.1098 | 2.3347 | 248 |
0.1096 | 2.3363 | 249 |
0.1063 | 2.3397 | 250 |
0.1053 | 2.3460 | 251 |
0.1077 | 2.3321 | 252 |
0.1055 | 2.3546 | 253 |
0.1053 | 2.3340 | 254 |
0.1041 | 2.3378 | 255 |
0.1027 | 2.3657 | 256 |
0.1030 | 2.3373 | 257 |
0.1018 | 2.3576 | 258 |
0.1040 | 2.3498 | 259 |
0.1010 | 2.3487 | 260 |
0.1011 | 2.3558 | 261 |
0.0999 | 2.3610 | 262 |
0.0996 | 2.3547 | 263 |
0.0989 | 2.3651 | 264 |
0.0987 | 2.3588 | 265 |
0.1003 | 2.3488 | 266 |
0.0966 | 2.3740 | 267 |
0.0973 | 2.3670 | 268 |
0.0980 | 2.3540 | 269 |
0.0977 | 2.3531 | 270 |
0.0956 | 2.3516 | 271 |
0.0940 | 2.3640 | 272 |
0.0941 | 2.3609 | 273 |
0.0933 | 2.3583 | 274 |
0.0954 | 2.3766 | 275 |
0.0905 | 2.3796 | 276 |
0.0931 | 2.3734 | 277 |
0.0924 | 2.3788 | 278 |
0.0897 | 2.3839 | 279 |
0.0900 | 2.3819 | 280 |
0.0900 | 2.3771 | 281 |
0.0913 | 2.3619 | 282 |
0.0888 | 2.3731 | 283 |
0.0901 | 2.3813 | 284 |
0.0877 | 2.3956 | 285 |
0.0882 | 2.3754 | 286 |
0.0874 | 2.3767 | 287 |
0.0862 | 2.3913 | 288 |
0.0877 | 2.3835 | 289 |
0.0864 | 2.4017 | 290 |
0.0858 | 2.4085 | 291 |
0.0863 | 2.4105 | 292 |
0.0858 | 2.4059 | 293 |
0.0865 | 2.3823 | 294 |
0.0843 | 2.4068 | 295 |
0.0849 | 2.4148 | 296 |
0.0838 | 2.4138 | 297 |
0.0837 | 2.4177 | 298 |
0.0824 | 2.4125 | 299 |
0.0830 | 2.3931 | 300 |
0.0827 | 2.4092 | 301 |
0.0840 | 2.4185 | 302 |
0.0835 | 2.4079 | 303 |
0.0814 | 2.4121 | 304 |
0.0820 | 2.4149 | 305 |
0.0811 | 2.3981 | 306 |
0.0815 | 2.4207 | 307 |
0.0795 | 2.4305 | 308 |
0.0816 | 2.4200 | 309 |
0.0792 | 2.4255 | 310 |
0.0803 | 2.4238 | 311 |
0.0781 | 2.4316 | 312 |
0.0773 | 2.4552 | 313 |
0.0777 | 2.4426 | 314 |
0.0767 | 2.4411 | 315 |
0.0775 | 2.4338 | 316 |
0.0774 | 2.4471 | 317 |
0.0775 | 2.4411 | 318 |
0.0772 | 2.4345 | 319 |
0.0767 | 2.4524 | 320 |
0.0773 | 2.4268 | 321 |
0.0764 | 2.4423 | 322 |
0.0763 | 2.4347 | 323 |
0.0757 | 2.4518 | 324 |
0.0761 | 2.4477 | 325 |
0.0742 | 2.4567 | 326 |
0.0763 | 2.4599 | 327 |
0.0745 | 2.4768 | 328 |
0.0751 | 2.4397 | 329 |
0.0744 | 2.4510 | 330 |
0.0737 | 2.4455 | 331 |
0.0747 | 2.4608 | 332 |
0.0724 | 2.4727 | 333 |
0.0740 | 2.4467 | 334 |
0.0739 | 2.4447 | 335 |
0.0716 | 2.4674 | 336 |
0.0723 | 2.4512 | 337 |
0.0726 | 2.4452 | 338 |
0.0709 | 2.4469 | 339 |
0.0721 | 2.4593 | 340 |
0.0719 | 2.4458 | 341 |
0.0704 | 2.4783 | 342 |
Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2