learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use 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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	9.1945	0.0	9.1945	3.0323
No log	2.0	4	8.0073	0.0	8.0073	2.8297
No log	3.0	6	7.0340	0.0	7.0340	2.6522
No log	4.0	8	6.3992	0.0	6.3992	2.5297
No log	5.0	10	5.7167	0.0186	5.7167	2.3910
No log	6.0	12	4.9700	0.0039	4.9700	2.2294
No log	7.0	14	4.3305	0.0039	4.3305	2.0810
No log	8.0	16	3.6304	0.0	3.6304	1.9054
No log	9.0	18	3.0178	0.0	3.0178	1.7372
No log	10.0	20	2.4044	0.0611	2.4044	1.5506
No log	11.0	22	1.8218	0.0382	1.8218	1.3497
No log	12.0	24	1.7765	0.0474	1.7765	1.3329
No log	13.0	26	1.3193	0.0316	1.3193	1.1486
No log	14.0	28	1.2736	0.0212	1.2736	1.1285
No log	15.0	30	1.2949	0.0106	1.2949	1.1380
No log	16.0	32	1.0736	0.0212	1.0736	1.0361
No log	17.0	34	0.9003	0.0508	0.9003	0.9488
No log	18.0	36	0.8202	0.3002	0.8202	0.9056
No log	19.0	38	0.7986	0.3086	0.7986	0.8936
No log	20.0	40	0.8425	0.2925	0.8425	0.9179
No log	21.0	42	0.6751	0.4368	0.6751	0.8216
No log	22.0	44	0.6710	0.4611	0.6710	0.8192
No log	23.0	46	0.6973	0.4354	0.6973	0.8350
No log	24.0	48	0.5971	0.4637	0.5971	0.7727
No log	25.0	50	0.6265	0.4694	0.6265	0.7915
No log	26.0	52	0.6278	0.4712	0.6278	0.7923
No log	27.0	54	0.6447	0.4636	0.6447	0.8029
No log	28.0	56	0.6297	0.4456	0.6297	0.7935
No log	29.0	58	0.8063	0.3877	0.8063	0.8980
No log	30.0	60	0.6576	0.3989	0.6576	0.8110
No log	31.0	62	0.6675	0.3929	0.6675	0.8170
No log	32.0	64	0.7013	0.3769	0.7013	0.8374
No log	33.0	66	0.6811	0.4367	0.6811	0.8253
No log	34.0	68	0.6828	0.4920	0.6828	0.8263
No log	35.0	70	0.7463	0.4469	0.7463	0.8639
No log	36.0	72	0.6860	0.5002	0.6860	0.8283
No log	37.0	74	0.8070	0.4497	0.8070	0.8983
No log	38.0	76	0.7599	0.4821	0.7599	0.8717
No log	39.0	78	0.6663	0.5318	0.6663	0.8163
No log	40.0	80	0.7374	0.4625	0.7374	0.8587
No log	41.0	82	0.5942	0.5359	0.5942	0.7708
No log	42.0	84	0.5987	0.5174	0.5987	0.7737
No log	43.0	86	1.0005	0.3286	1.0005	1.0002
No log	44.0	88	1.0885	0.3020	1.0885	1.0433
No log	45.0	90	0.6541	0.5001	0.6541	0.8088
No log	46.0	92	0.6706	0.4948	0.6706	0.8189
No log	47.0	94	0.6553	0.4731	0.6553	0.8095
No log	48.0	96	1.0693	0.2845	1.0693	1.0341
No log	49.0	98	0.9424	0.3342	0.9424	0.9708
No log	50.0	100	0.8037	0.4080	0.8037	0.8965
No log	51.0	102	0.7984	0.4369	0.7984	0.8935
No log	52.0	104	0.9939	0.3262	0.9939	0.9970
No log	53.0	106	1.0229	0.2995	1.0229	1.0114
No log	54.0	108	0.7958	0.4371	0.7958	0.8921
No log	55.0	110	0.6327	0.4868	0.6327	0.7954
No log	56.0	112	0.6914	0.4809	0.6914	0.8315

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Trial3BERT_AugV8_k1_task1_organization_sp030_lw010_fold0

Trial3BERT_AugV8_k1_task1_organization_sp030_lw010_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_sp030_lw010_fold0