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	2	9.8683	0.0	9.8683	3.1414
No log	2.0	4	9.2970	0.0	9.2970	3.0491
No log	3.0	6	8.2559	0.0	8.2559	2.8733
No log	4.0	8	6.7312	0.0	6.7312	2.5945
No log	5.0	10	5.3089	0.0139	5.3089	2.3041
No log	6.0	12	4.4659	0.0115	4.4659	2.1133
No log	7.0	14	3.2871	0.0	3.2871	1.8130
No log	8.0	16	2.5632	0.0146	2.5632	1.6010
No log	9.0	18	1.9377	0.0511	1.9377	1.3920
No log	10.0	20	1.4832	0.0316	1.4832	1.2179
No log	11.0	22	1.1910	0.0316	1.1910	1.0913
No log	12.0	24	0.9417	0.0316	0.9417	0.9704
No log	13.0	26	0.8525	0.2803	0.8525	0.9233
No log	14.0	28	0.7437	0.2444	0.7437	0.8624
No log	15.0	30	0.6743	0.2849	0.6743	0.8211
No log	16.0	32	0.6370	0.4136	0.6370	0.7981
No log	17.0	34	0.6171	0.4553	0.6171	0.7856
No log	18.0	36	0.5363	0.4635	0.5363	0.7323
No log	19.0	38	0.5738	0.5311	0.5738	0.7575
No log	20.0	40	0.4929	0.4378	0.4929	0.7021
No log	21.0	42	0.5566	0.5273	0.5566	0.7461
No log	22.0	44	0.8078	0.4560	0.8078	0.8988
No log	23.0	46	0.5032	0.5272	0.5032	0.7094
No log	24.0	48	0.5034	0.5252	0.5034	0.7095
No log	25.0	50	1.2187	0.2971	1.2187	1.1039
No log	26.0	52	1.4281	0.2362	1.4281	1.1950
No log	27.0	54	0.6690	0.4768	0.6690	0.8180
No log	28.0	56	0.6167	0.4960	0.6167	0.7853
No log	29.0	58	0.6153	0.4545	0.6153	0.7844
No log	30.0	60	0.5865	0.4391	0.5865	0.7658
No log	31.0	62	0.6015	0.4706	0.6015	0.7756
No log	32.0	64	0.6287	0.5083	0.6287	0.7929
No log	33.0	66	0.6036	0.5213	0.6036	0.7769
No log	34.0	68	0.5857	0.5497	0.5857	0.7653
No log	35.0	70	0.5752	0.5586	0.5752	0.7584
No log	36.0	72	0.5564	0.5467	0.5564	0.7460
No log	37.0	74	0.5629	0.5247	0.5629	0.7503
No log	38.0	76	0.5499	0.5290	0.5499	0.7416
No log	39.0	78	0.6033	0.5062	0.6033	0.7767
No log	40.0	80	0.5557	0.5314	0.5557	0.7455
No log	41.0	82	0.5638	0.5308	0.5638	0.7509
No log	42.0	84	0.5979	0.5053	0.5979	0.7732
No log	43.0	86	0.5866	0.5077	0.5866	0.7659
No log	44.0	88	0.5881	0.5105	0.5881	0.7669
No log	45.0	90	0.5968	0.5030	0.5968	0.7725
No log	46.0	92	0.5776	0.5244	0.5776	0.7600
No log	47.0	94	0.5636	0.5343	0.5636	0.7507
No log	48.0	96	0.6769	0.4733	0.6769	0.8227
No log	49.0	98	0.6067	0.5271	0.6067	0.7789
No log	50.0	100	0.5772	0.5492	0.5772	0.7598
No log	51.0	102	0.6225	0.5044	0.6225	0.7890
No log	52.0	104	0.7125	0.4764	0.7125	0.8441
No log	53.0	106	0.6353	0.4969	0.6353	0.7970
No log	54.0	108	0.5694	0.5378	0.5694	0.7546
No log	55.0	110	0.5699	0.5449	0.5699	0.7549
No log	56.0	112	0.5649	0.4968	0.5649	0.7516
No log	57.0	114	0.6318	0.4491	0.6318	0.7949
No log	58.0	116	0.5495	0.4940	0.5495	0.7413
No log	59.0	118	0.5482	0.4956	0.5482	0.7404
No log	60.0	120	0.5698	0.5097	0.5698	0.7549
No log	61.0	122	0.5491	0.5457	0.5491	0.7410
No log	62.0	124	0.5557	0.5619	0.5557	0.7454
No log	63.0	126	0.6114	0.5153	0.6114	0.7819
No log	64.0	128	0.6294	0.5114	0.6294	0.7933
No log	65.0	130	0.5845	0.5133	0.5845	0.7645
No log	66.0	132	0.5534	0.5327	0.5534	0.7439
No log	67.0	134	0.5577	0.5211	0.5577	0.7468
No log	68.0	136	0.5472	0.5125	0.5472	0.7397
No log	69.0	138	0.5646	0.5048	0.5646	0.7514
No log	70.0	140	0.5974	0.5007	0.5974	0.7729
No log	71.0	142	0.5840	0.5016	0.5840	0.7642
No log	72.0	144	0.5318	0.5105	0.5318	0.7292
No log	73.0	146	0.5279	0.5179	0.5279	0.7265
No log	74.0	148	0.5809	0.5192	0.5809	0.7622
No log	75.0	150	0.5944	0.5217	0.5944	0.7710
No log	76.0	152	0.5609	0.5075	0.5609	0.7490
No log	77.0	154	0.5427	0.5187	0.5427	0.7367
No log	78.0	156	0.5745	0.5081	0.5745	0.7580
No log	79.0	158	0.5796	0.5200	0.5796	0.7613
No log	80.0	160	0.5491	0.5292	0.5491	0.7410
No log	81.0	162	0.5499	0.5357	0.5499	0.7415
No log	82.0	164	0.5760	0.5152	0.5760	0.7589
No log	83.0	166	0.6303	0.4889	0.6303	0.7939
No log	84.0	168	0.6190	0.4939	0.6190	0.7867
No log	85.0	170	0.5688	0.5122	0.5688	0.7542
No log	86.0	172	0.5503	0.5221	0.5503	0.7418
No log	87.0	174	0.5565	0.5188	0.5565	0.7460
No log	88.0	176	0.5804	0.5216	0.5804	0.7618
No log	89.0	178	0.5894	0.5031	0.5894	0.7677
No log	90.0	180	0.5739	0.5205	0.5739	0.7576
No log	91.0	182	0.5443	0.5207	0.5443	0.7378
No log	92.0	184	0.5304	0.5266	0.5304	0.7283

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

genki10/BERT_V8_sp10_lw40_ex50_lo50_k2_k2_fold0

BERT_V8_sp10_lw40_ex50_lo50_k2_k2_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_V8_sp10_lw40_ex50_lo50_k2_k2_fold0