| | --- |
| | tags: |
| | - generated_from_keras_callback |
| | model-index: |
| | - name: pretrained-m-bert-200 |
| | 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. --> |
| |
|
| | # pretrained-m-bert-200 |
| |
|
| | This model is a fine-tuned version of [](https://huggingface.co/) 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 |
| |
|
