bert_12_layer_model_v1_complete_training

This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Accuracy
6.1779	0.11	10000	6.1719	0.1487
4.6914	0.22	20000	4.5039	0.3178
3.2325	0.33	30000	3.0977	0.4772
2.831	0.44	40000	2.7266	0.5224
2.6262	0.55	50000	2.5371	0.5455
2.5006	0.66	60000	2.4141	0.5614
2.4062	0.76	70000	2.3242	0.5734
2.3338	0.87	80000	2.2539	0.5823
2.2838	0.98	90000	2.2012	0.5894
2.231	1.09	100000	2.1504	0.5959
2.1903	1.2	110000	2.1133	0.6009
2.1594	1.31	120000	2.0801	0.6054
2.1307	1.42	130000	2.0488	0.6095
2.0948	1.53	140000	2.0234	0.6133
2.0748	1.64	150000	1.9980	0.6169
2.0572	1.75	160000	1.9756	0.6195
2.0359	1.86	170000	1.9551	0.6225
2.0148	1.97	180000	1.9385	0.6251
1.9994	2.08	190000	1.9219	0.6274
1.9769	2.18	200000	1.9043	0.6297
1.9705	2.29	210000	1.8916	0.6317
1.9557	2.4	220000	1.8779	0.6338
1.9407	2.51	230000	1.8643	0.6354
1.9307	2.62	240000	1.8525	0.6372
1.9186	2.73	250000	1.8408	0.6388
1.9114	2.84	260000	1.8320	0.6401
1.896	2.95	270000	1.8213	0.6419
1.8857	3.06	280000	1.8115	0.6433
1.8752	3.17	290000	1.8037	0.6443
1.8662	3.28	300000	1.7949	0.6457
1.8575	3.39	310000	1.7871	0.6470
1.8538	3.5	320000	1.7793	0.6478
1.8426	3.6	330000	1.7734	0.6489
1.8389	3.71	340000	1.7646	0.6501
1.8278	3.82	350000	1.7598	0.6511
1.8319	3.93	360000	1.7529	0.6520
1.8203	4.04	370000	1.7471	0.6527
1.8162	4.15	380000	1.7412	0.6536
1.8113	4.26	390000	1.7373	0.6543
1.8055	4.37	400000	1.7324	0.6551
1.7991	4.48	410000	1.7285	0.6556
1.7965	4.59	420000	1.7246	0.6562
1.7938	4.7	430000	1.7207	0.6567
1.793	4.81	440000	1.7178	0.6571
1.7848	4.92	450000	1.7148	0.6576