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pretrained-m-bert-200
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 5.6892
- Validation Loss: 15.9999
- 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': 'Adam', 'learning_rate': 1e-04, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 10.2629 | 10.9400 | 0 |
| 7.8719 | 10.8986 | 1 |
| 6.8337 | 11.4901 | 2 |
| 6.4663 | 11.6037 | 3 |
| 6.4171 | 11.5051 | 4 |
| 6.3166 | 12.1207 | 5 |
| 6.4304 | 11.7927 | 6 |
| 6.0435 | 12.1347 | 7 |
| 5.9134 | 12.1229 | 8 |
| 6.0124 | 12.0225 | 9 |
| 5.9096 | 12.4855 | 10 |
| 5.8829 | 12.7256 | 11 |
| 5.8533 | 12.3504 | 12 |
| 5.8075 | 12.7843 | 13 |
| 6.0418 | 12.6493 | 14 |
| 5.8611 | 12.4900 | 15 |
| 5.8863 | 12.7790 | 16 |
| 5.9484 | 13.0246 | 17 |
| 5.8226 | 12.9865 | 18 |
| 5.8262 | 13.1064 | 19 |
| 5.8687 | 13.1811 | 20 |
| 5.7531 | 13.2824 | 21 |
| 5.8473 | 13.2894 | 22 |
| 5.8762 | 13.1719 | 23 |
| 5.7386 | 13.0748 | 24 |
| 5.6647 | 13.3089 | 25 |
| 5.8553 | 13.5698 | 26 |
| 5.7698 | 14.1035 | 27 |
| 5.7972 | 13.6096 | 28 |
| 5.9381 | 13.1142 | 29 |
| 5.8173 | 13.1007 | 30 |
| 5.7676 | 13.6502 | 31 |
| 5.9740 | 13.5317 | 32 |
| 5.6842 | 13.7206 | 33 |
| 5.7764 | 13.5819 | 34 |
| 5.7659 | 13.4004 | 35 |
| 5.7104 | 13.6715 | 36 |
| 5.8345 | 13.5589 | 37 |
| 5.8067 | 13.6957 | 38 |
| 5.8537 | 13.6661 | 39 |
| 5.6418 | 13.8966 | 40 |
| 5.7818 | 13.7630 | 41 |
| 5.7406 | 14.1682 | 42 |
| 5.7053 | 13.8797 | 43 |
| 5.7151 | 14.1307 | 44 |
| 5.6621 | 14.1855 | 45 |
| 5.6716 | 14.1013 | 46 |
| 5.6596 | 14.2236 | 47 |
| 5.6680 | 14.0390 | 48 |
| 5.8122 | 14.0500 | 49 |
| 5.8497 | 14.0991 | 50 |
| 5.6758 | 14.5258 | 51 |
| 5.7158 | 14.2373 | 52 |
| 5.7288 | 13.9851 | 53 |
| 5.9239 | 14.2297 | 54 |
| 5.6722 | 13.6866 | 55 |
| 5.8708 | 14.2755 | 56 |
| 5.7190 | 14.4764 | 57 |
| 5.7218 | 14.1861 | 58 |
| 5.7478 | 14.3363 | 59 |
| 5.7843 | 13.9645 | 60 |
| 5.6555 | 14.1351 | 61 |
| 5.6951 | 14.5155 | 62 |
| 5.6711 | 14.4671 | 63 |
| 5.7068 | 14.4064 | 64 |
| 5.7773 | 14.5143 | 65 |
| 5.7188 | 14.6878 | 66 |
| 5.7912 | 14.3496 | 67 |
| 5.9308 | 14.4187 | 68 |
| 5.8765 | 14.6648 | 69 |
| 5.7103 | 14.3686 | 70 |
| 5.6585 | 14.3171 | 71 |
| 5.8697 | 14.2778 | 72 |
| 5.6874 | 14.1511 | 73 |
| 5.7367 | 15.0222 | 74 |
| 5.8603 | 14.2226 | 75 |
| 5.8183 | 14.6257 | 76 |
| 5.7646 | 14.5472 | 77 |
| 5.7813 | 14.4560 | 78 |
| 5.6991 | 14.1486 | 79 |
| 5.7365 | 14.5998 | 80 |
| 5.7602 | 14.3595 | 81 |
| 5.7646 | 14.4916 | 82 |
| 5.6289 | 15.1076 | 83 |
| 5.8171 | 14.7216 | 84 |
| 5.7939 | 14.9316 | 85 |
| 5.8249 | 14.6632 | 86 |
| 5.6479 | 15.2074 | 87 |
| 5.7985 | 14.9238 | 88 |
| 5.7332 | 14.4504 | 89 |
| 5.7495 | 14.2924 | 90 |
| 5.7579 | 15.3362 | 91 |
| 5.7217 | 15.0819 | 92 |
| 5.6750 | 14.9618 | 93 |
| 5.8607 | 14.6850 | 94 |
| 5.6310 | 14.9199 | 95 |
| 5.7532 | 14.8353 | 96 |
| 5.6318 | 14.9707 | 97 |
| 5.6861 | 14.8903 | 98 |
| 5.7634 | 15.3237 | 99 |
| 5.7703 | 15.0675 | 100 |
| 5.7290 | 15.5422 | 101 |
| 5.8383 | 14.9575 | 102 |
| 5.7694 | 14.2810 | 103 |
| 5.6092 | 15.5547 | 104 |
| 5.7699 | 15.2309 | 105 |
| 5.8225 | 15.0764 | 106 |
| 5.8007 | 14.8694 | 107 |
| 5.7435 | 15.2683 | 108 |
| 5.7358 | 15.3533 | 109 |
| 5.8024 | 14.8301 | 110 |
| 5.8027 | 15.3505 | 111 |
| 5.8282 | 15.1353 | 112 |
| 5.6818 | 15.3525 | 113 |
| 5.8653 | 14.7720 | 114 |
| 5.7234 | 15.2079 | 115 |
| 5.8179 | 14.9355 | 116 |
| 5.6718 | 15.2269 | 117 |
| 5.8428 | 15.1447 | 118 |
| 5.6875 | 15.2709 | 119 |
| 5.7212 | 15.1541 | 120 |
| 5.8223 | 15.2145 | 121 |
| 5.7125 | 15.2783 | 122 |
| 5.7707 | 15.6087 | 123 |
| 5.7251 | 15.1095 | 124 |
| 5.6308 | 15.2443 | 125 |
| 5.7163 | 15.7562 | 126 |
| 5.7097 | 15.5930 | 127 |
| 5.6560 | 15.1742 | 128 |
| 5.9121 | 15.0983 | 129 |
| 5.5284 | 15.4298 | 130 |
| 5.7584 | 15.5905 | 131 |
| 5.8737 | 15.3326 | 132 |
| 5.7731 | 15.6967 | 133 |
| 5.6686 | 15.2850 | 134 |
| 5.7585 | 15.2779 | 135 |
| 5.7239 | 15.6021 | 136 |
| 5.7295 | 15.3237 | 137 |
| 5.7358 | 15.3199 | 138 |
| 5.8334 | 14.8834 | 139 |
| 5.6537 | 15.6226 | 140 |
| 5.6501 | 15.2466 | 141 |
| 5.7591 | 14.9815 | 142 |
| 5.7694 | 15.3828 | 143 |
| 5.7239 | 15.4082 | 144 |
| 5.8641 | 14.8029 | 145 |
| 5.7668 | 15.4207 | 146 |
| 5.7180 | 15.8702 | 147 |
| 5.6461 | 15.7631 | 148 |
| 5.8629 | 15.2891 | 149 |
| 5.7973 | 15.9778 | 150 |
| 5.8458 | 15.4747 | 151 |
| 5.7720 | 15.9476 | 152 |
| 5.6491 | 15.2055 | 153 |
| 5.7801 | 15.3822 | 154 |
| 5.8175 | 15.7697 | 155 |
| 5.7536 | 15.2464 | 156 |
| 5.7925 | 15.4849 | 157 |
| 5.6012 | 15.5773 | 158 |
| 5.7623 | 15.7559 | 159 |
| 5.7078 | 15.7061 | 160 |
| 5.7834 | 15.5417 | 161 |
| 5.7058 | 15.3236 | 162 |
| 5.8079 | 15.1048 | 163 |
| 5.7757 | 15.2895 | 164 |
| 5.6822 | 15.9946 | 165 |
| 5.6205 | 15.8053 | 166 |
| 5.8778 | 15.9524 | 167 |
| 5.7211 | 15.5006 | 168 |
| 5.7499 | 15.7000 | 169 |
| 5.6561 | 16.1970 | 170 |
| 5.7077 | 15.7324 | 171 |
| 5.7177 | 15.8832 | 172 |
| 5.8901 | 15.2579 | 173 |
| 5.6842 | 16.1185 | 174 |
| 5.7424 | 15.8840 | 175 |
| 5.6889 | 15.5184 | 176 |
| 5.7339 | 15.9269 | 177 |
| 5.6635 | 15.8283 | 178 |
| 5.7331 | 16.0767 | 179 |
| 5.7096 | 15.7523 | 180 |
| 5.6715 | 16.0680 | 181 |
| 5.7703 | 15.6030 | 182 |
| 5.6772 | 15.6442 | 183 |
| 5.7933 | 15.6118 | 184 |
| 5.6788 | 15.5001 | 185 |
| 5.6985 | 15.4559 | 186 |
| 5.8450 | 15.5850 | 187 |
| 5.7437 | 15.9233 | 188 |
| 5.7502 | 15.8410 | 189 |
| 5.7081 | 16.0491 | 190 |
| 5.8119 | 15.3163 | 191 |
| 5.7426 | 15.7990 | 192 |
| 5.6422 | 15.9709 | 193 |
| 5.7431 | 15.3411 | 194 |
| 5.7894 | 15.5860 | 195 |
| 5.5432 | 16.2503 | 196 |
| 5.7073 | 16.0347 | 197 |
| 5.6637 | 16.2954 | 198 |
| 5.6892 | 15.9999 | 199 |
Framework versions
- Transformers 4.27.0.dev0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2
