generated_from_keras_callback

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TimShieh/bert-base-cased-finetuned-semeval2017-MLM-tf

This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

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:

Training results

Train Loss Validation Loss Epoch
2.8433 2.6662 0
2.7598 2.5861 1
2.7534 2.5040 2
2.7240 2.4523 3
2.6318 2.5183 4
2.5957 2.4422 5
2.5625 2.4058 6
2.5154 2.3935 7
2.4640 2.3379 8
2.4819 2.3405 9
2.4415 2.3790 10
2.3893 2.3233 11
2.3388 2.3790 12
2.3699 2.3036 13
2.2846 2.2498 14
2.3063 2.2773 15
2.2476 2.2761 16
2.1773 2.2033 17
2.2143 2.2317 18
2.2070 2.2894 19
2.1538 2.2133 20
2.0956 2.3578 21
2.1071 2.2503 22
2.0790 2.3071 23
2.0288 2.3034 24
2.0533 2.3170 25
2.0120 2.2095 26
1.9467 2.2245 27
1.9542 2.2078 28
1.9432 2.3161 29
1.9461 2.3124 30
1.9065 2.2365 31
1.8745 2.1271 32
1.8496 2.3026 33
1.8842 2.3762 34
1.8175 2.2070 35
1.8243 2.2866 36
1.7952 2.2107 37
1.7777 2.3179 38
1.7657 2.2338 39
1.7292 2.2267 40
1.7378 2.2141 41
1.6489 2.2372 42
1.6734 2.2508 43
1.6657 2.2625 44
1.6595 2.3270 45
1.6092 2.2561 46
1.5995 2.1516 47
1.6329 2.3223 48
1.6295 2.3140 49
1.5856 2.2300 50
1.6024 2.2130 51
1.5409 2.1686 52
1.5413 2.2330 53
1.5623 2.3331 54
1.5061 2.2902 55
1.5053 2.3790 56
1.5196 2.2583 57
1.4747 2.2444 58
1.5104 2.3633 59
1.4382 2.3433 60
1.4945 2.2789 61
1.4732 2.2114 62
1.4642 2.2824 63
1.4017 2.3451 64
1.4142 2.2902 65
1.3868 2.3788 66
1.4233 2.2854 67
1.4314 2.4351 68
1.3653 2.2845 69
1.4202 2.2994 70
1.3817 2.2924 71
1.3771 2.3026 72
1.3795 2.2778 73
1.3843 2.3807 74
1.3457 2.3068 75
1.3408 2.3956 76
1.3737 2.2845 77
1.3277 2.3673 78
1.3330 2.3530 79
1.2938 2.2045 80
1.3352 2.3202 81
1.3095 2.3502 82
1.2982 2.2561 83
1.3452 2.2632 84
1.2995 2.3359 85
1.3235 2.2482 86
1.3153 2.3753 87
1.3092 2.3334 88
1.3178 2.4354 89
1.3300 2.3763 90
1.3079 2.3011 91
1.2800 2.3430 92
1.3166 2.2550 93
1.2893 2.3375 94
1.2898 2.3382 95
1.3280 2.4488 96
1.3429 2.3147 97
1.3086 2.3846 98

Framework versions