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	11.8191	0.0163	11.8194	3.4379
No log	2.0	4	9.7805	0.0012	9.7808	3.1274
No log	3.0	6	7.3231	0.0	7.3235	2.7062
No log	4.0	8	5.6979	0.0529	5.6982	2.3871
No log	5.0	10	4.3393	0.0199	4.3396	2.0832
No log	6.0	12	3.3599	0.0	3.3602	1.8331
No log	7.0	14	2.6822	0.0	2.6825	1.6378
No log	8.0	16	2.1142	0.1292	2.1146	1.4542
No log	9.0	18	1.8618	0.1363	1.8623	1.3646
No log	10.0	20	1.3918	0.0552	1.3922	1.1799
No log	11.0	22	1.1954	0.0241	1.1957	1.0935
No log	12.0	24	1.1181	0.1314	1.1183	1.0575
No log	13.0	26	1.5286	0.1851	1.5287	1.2364
No log	14.0	28	1.0816	0.4456	1.0816	1.0400
No log	15.0	30	0.8765	0.1267	0.8767	0.9363
No log	16.0	32	0.9555	-0.0160	0.9557	0.9776
No log	17.0	34	0.7673	0.2726	0.7674	0.8760
No log	18.0	36	0.6773	0.4197	0.6771	0.8228
No log	19.0	38	0.8951	0.3515	0.8944	0.9457
No log	20.0	40	0.9680	0.3453	0.9668	0.9833
No log	21.0	42	0.9069	0.4627	0.9063	0.9520
No log	22.0	44	0.8769	0.4643	0.8762	0.9361
No log	23.0	46	0.7811	0.4345	0.7801	0.8833
No log	24.0	48	0.6724	0.4305	0.6716	0.8195
No log	25.0	50	0.7559	0.3031	0.7552	0.8690
No log	26.0	52	0.7026	0.3658	0.7021	0.8379
No log	27.0	54	0.7092	0.4561	0.7087	0.8418
No log	28.0	56	1.0685	0.2440	1.0673	1.0331
No log	29.0	58	1.0512	0.2944	1.0499	1.0247
No log	30.0	60	0.7153	0.5030	0.7153	0.8458
No log	31.0	62	0.7871	0.4885	0.7871	0.8872
No log	32.0	64	0.6683	0.5210	0.6679	0.8173
No log	33.0	66	1.0990	0.1600	1.0980	1.0479
No log	34.0	68	1.0415	0.1703	1.0406	1.0201
No log	35.0	70	0.6982	0.4833	0.6977	0.8353
No log	36.0	72	0.7340	0.4999	0.7336	0.8565
No log	37.0	74	0.7492	0.4944	0.7487	0.8653
No log	38.0	76	0.7950	0.4247	0.7942	0.8912
No log	39.0	78	0.8962	0.2977	0.8954	0.9462
No log	40.0	80	0.7601	0.4415	0.7591	0.8713
No log	41.0	82	0.7120	0.5674	0.7112	0.8433
No log	42.0	84	0.6512	0.5854	0.6503	0.8064
No log	43.0	86	0.7364	0.4563	0.7354	0.8576
No log	44.0	88	0.7287	0.4406	0.7278	0.8531
No log	45.0	90	0.6523	0.5308	0.6513	0.8070
No log	46.0	92	0.7663	0.5055	0.7652	0.8748
No log	47.0	94	0.9009	0.3854	0.8998	0.9486
No log	48.0	96	1.0153	0.2550	1.0144	1.0072
No log	49.0	98	1.0178	0.2512	1.0170	1.0085
No log	50.0	100	0.8240	0.4076	0.8232	0.9073
No log	51.0	102	0.6468	0.4655	0.6461	0.8038
No log	52.0	104	0.6438	0.5657	0.6430	0.8019
No log	53.0	106	0.6511	0.5472	0.6502	0.8064
No log	54.0	108	0.7823	0.4035	0.7813	0.8839
No log	55.0	110	0.8616	0.3495	0.8607	0.9277
No log	56.0	112	0.8810	0.4355	0.8800	0.9381
No log	57.0	114	0.9686	0.3122	0.9679	0.9838

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_sp020_lw040_fold2

Trial3BERT_AugV8_k1_task1_organization_sp020_lw040_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_sp020_lw040_fold2