learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	1	10.6090	0.0218	10.6098	3.2573
No log	2.0	2	9.6424	0.0	9.6427	3.1053
No log	3.0	3	9.4016	0.0	9.4018	3.0662
No log	4.0	4	9.2154	0.0	9.2155	3.0357
No log	5.0	5	9.0159	0.0	9.0160	3.0027
No log	6.0	6	8.7749	0.0	8.7751	2.9623
No log	7.0	7	8.4236	0.0	8.4237	2.9024
No log	8.0	8	7.7623	0.0	7.7625	2.7861
No log	9.0	9	6.8367	0.0	6.8370	2.6148
No log	10.0	10	6.7606	0.0	6.7607	2.6001
No log	11.0	11	6.3592	-0.0012	6.3594	2.5218
No log	12.0	12	5.7604	0.0148	5.7606	2.4001
No log	13.0	13	5.3356	0.0039	5.3359	2.3100
No log	14.0	14	4.9974	0.0039	4.9977	2.2356
No log	15.0	15	4.6370	0.0039	4.6373	2.1534
No log	16.0	16	4.2154	0.0	4.2158	2.0532
No log	17.0	17	3.7720	0.0	3.7724	1.9423
No log	18.0	18	3.4500	0.0	3.4504	1.8575
No log	19.0	19	3.2373	0.0	3.2377	1.7994
No log	20.0	20	2.9924	0.0	2.9928	1.7300
No log	21.0	21	2.7789	0.0	2.7794	1.6671
No log	22.0	22	2.6818	0.0	2.6822	1.6377
No log	23.0	23	2.6036	0.0088	2.6040	1.6137
No log	24.0	24	2.4093	0.0699	2.4097	1.5523
No log	25.0	25	2.1542	0.0676	2.1546	1.4679
No log	26.0	26	1.9393	0.0280	1.9397	1.3927
No log	27.0	27	1.7809	0.0107	1.7813	1.3347
No log	28.0	28	1.6486	0.0107	1.6490	1.2841
No log	29.0	29	1.5388	0.0107	1.5393	1.2407
No log	30.0	30	1.4466	0.0107	1.4471	1.2030
No log	31.0	31	1.3580	0.0107	1.3584	1.1655
No log	32.0	32	1.2841	0.0107	1.2845	1.1334
No log	33.0	33	1.2151	0.0107	1.2155	1.1025
No log	34.0	34	1.1457	0.0107	1.1461	1.0706
No log	35.0	35	1.0715	0.0107	1.0719	1.0353
No log	36.0	36	1.0069	0.0107	1.0073	1.0036
No log	37.0	37	0.9393	0.0174	0.9397	0.9694
No log	38.0	38	0.8821	0.0241	0.8824	0.9394
No log	39.0	39	0.8444	0.1786	0.8447	0.9191
No log	40.0	40	0.8393	0.2700	0.8395	0.9163
No log	41.0	41	0.8123	0.3427	0.8125	0.9014
No log	42.0	42	0.8893	0.3743	0.8894	0.9431
No log	43.0	43	0.9838	0.3566	0.9839	0.9919
No log	44.0	44	0.8190	0.4483	0.8190	0.9050
No log	45.0	45	0.7829	0.4651	0.7829	0.8848
No log	46.0	46	1.0299	0.3558	1.0300	1.0149
No log	47.0	47	1.0436	0.3534	1.0436	1.0216
No log	48.0	48	0.8346	0.4361	0.8345	0.9135
No log	49.0	49	0.7360	0.4637	0.7359	0.8578
No log	50.0	50	0.9647	0.3994	0.9645	0.9821
No log	51.0	51	1.6842	0.2577	1.6838	1.2976
No log	52.0	52	1.9496	0.1995	1.9491	1.3961
No log	53.0	53	1.7009	0.2448	1.7001	1.3039
No log	54.0	54	1.1225	0.3753	1.1215	1.0590
No log	55.0	55	0.9849	0.4157	0.9840	0.9920
No log	56.0	56	1.1284	0.3864	1.1274	1.0618
No log	57.0	57	1.5792	0.2519	1.5781	1.2562
No log	58.0	58	1.7197	0.2316	1.7188	1.3110
No log	59.0	59	1.5287	0.2468	1.5278	1.2360
No log	60.0	60	1.1270	0.3714	1.1261	1.0612
No log	61.0	61	0.8004	0.4614	0.7996	0.8942
No log	62.0	62	0.7457	0.4728	0.7450	0.8631
No log	63.0	63	0.8401	0.4679	0.8392	0.9161
No log	64.0	64	1.1192	0.3555	1.1182	1.0575
No log	65.0	65	1.5189	0.2665	1.5179	1.2320
No log	66.0	66	1.6861	0.2252	1.6851	1.2981
No log	67.0	67	1.6131	0.2417	1.6119	1.2696
No log	68.0	68	1.3614	0.2790	1.3601	1.1662
No log	69.0	69	1.1044	0.3768	1.1031	1.0503
No log	70.0	70	1.0304	0.4033	1.0291	1.0144
No log	71.0	71	1.0695	0.3896	1.0681	1.0335
No log	72.0	72	1.2226	0.3343	1.2213	1.1051
No log	73.0	73	1.5133	0.2582	1.5120	1.2297
No log	74.0	74	1.6382	0.2367	1.6370	1.2794
No log	75.0	75	1.5982	0.2548	1.5970	1.2637
No log	76.0	76	1.4322	0.2705	1.4309	1.1962
No log	77.0	77	1.2073	0.3464	1.2061	1.0982
No log	78.0	78	1.0687	0.3897	1.0674	1.0331
No log	79.0	79	1.0546	0.4023	1.0532	1.0263
No log	80.0	80	1.1116	0.3854	1.1102	1.0537
No log	81.0	81	1.2341	0.3442	1.2327	1.1103
No log	82.0	82	1.3885	0.2755	1.3871	1.1778
No log	83.0	83	1.4612	0.2590	1.4598	1.2082
No log	84.0	84	1.4540	0.2573	1.4526	1.2052
No log	85.0	85	1.3795	0.2771	1.3780	1.1739
No log	86.0	86	1.2956	0.3122	1.2942	1.1376
No log	87.0	87	1.2848	0.3174	1.2834	1.1329
No log	88.0	88	1.2867	0.3101	1.2853	1.1337
No log	89.0	89	1.3207	0.2926	1.3193	1.1486
No log	90.0	90	1.3071	0.3002	1.3057	1.1427
No log	91.0	91	1.2771	0.3088	1.2758	1.1295
No log	92.0	92	1.2248	0.3334	1.2234	1.1061

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

genki10/BERT_V8_sp10_lw40_ex100_lo100_k1_k1_fold2

BERT_V8_sp10_lw40_ex100_lo100_k1_k1_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_V8_sp10_lw40_ex100_lo100_k1_k1_fold2