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	8.5416	0.0	8.5416	2.9226
No log	2.0	4	7.5558	0.0	7.5556	2.7487
No log	3.0	6	5.4210	0.0298	5.4212	2.3283
No log	4.0	8	4.2906	0.0039	4.2909	2.0714
No log	5.0	10	3.5173	0.0	3.5177	1.8755
No log	6.0	12	2.7716	0.0	2.7720	1.6649
No log	7.0	14	2.2150	0.1497	2.2155	1.4884
No log	8.0	16	1.7161	0.0449	1.7166	1.3102
No log	9.0	18	1.3676	0.0345	1.3680	1.1696
No log	10.0	20	1.1180	0.0345	1.1184	1.0575
No log	11.0	22	0.9636	0.0174	0.9640	0.9818
No log	12.0	24	0.8114	0.2565	0.8117	0.9009
No log	13.0	26	0.8295	0.3356	0.8298	0.9109
No log	14.0	28	0.7784	0.4046	0.7786	0.8824
No log	15.0	30	0.7157	0.4639	0.7159	0.8461
No log	16.0	32	0.8796	0.3855	0.8799	0.9380
No log	17.0	34	0.7711	0.4132	0.7713	0.8783
No log	18.0	36	0.5657	0.5435	0.5659	0.7522
No log	19.0	38	0.5213	0.5519	0.5213	0.7220
No log	20.0	40	0.8553	0.4221	0.8554	0.9249
No log	21.0	42	1.0186	0.3828	1.0186	1.0093
No log	22.0	44	0.6033	0.5193	0.6034	0.7768
No log	23.0	46	0.6203	0.3562	0.6203	0.7876
No log	24.0	48	0.6809	0.3388	0.6808	0.8251
No log	25.0	50	0.5908	0.4547	0.5907	0.7686
No log	26.0	52	0.5925	0.4969	0.5924	0.7697
No log	27.0	54	0.5732	0.5066	0.5728	0.7569
No log	28.0	56	0.5894	0.5158	0.5890	0.7674
No log	29.0	58	0.5224	0.5518	0.5220	0.7225
No log	30.0	60	0.6489	0.4999	0.6487	0.8054
No log	31.0	62	0.6063	0.5125	0.6061	0.7785
No log	32.0	64	0.5335	0.5921	0.5331	0.7301
No log	33.0	66	0.5717	0.5600	0.5712	0.7558
No log	34.0	68	0.6256	0.5524	0.6251	0.7906
No log	35.0	70	0.6772	0.5335	0.6767	0.8226
No log	36.0	72	0.6776	0.5141	0.6769	0.8228
No log	37.0	74	0.6876	0.5184	0.6869	0.8288
No log	38.0	76	0.6222	0.5373	0.6218	0.7886
No log	39.0	78	0.9012	0.3353	0.9010	0.9492
No log	40.0	80	0.7947	0.4076	0.7945	0.8913
No log	41.0	82	0.5803	0.5734	0.5799	0.7615
No log	42.0	84	0.6138	0.5749	0.6131	0.7830
No log	43.0	86	0.6350	0.6009	0.6343	0.7964
No log	44.0	88	0.7929	0.4975	0.7924	0.8902
No log	45.0	90	0.7383	0.5029	0.7380	0.8590
No log	46.0	92	0.6282	0.5638	0.6276	0.7922
No log	47.0	94	0.6450	0.5072	0.6446	0.8028
No log	48.0	96	0.6500	0.4708	0.6499	0.8062
No log	49.0	98	0.6633	0.4676	0.6633	0.8144
No log	50.0	100	0.6159	0.4990	0.6157	0.7846
No log	51.0	102	0.5913	0.5701	0.5909	0.7687
No log	52.0	104	0.5992	0.5638	0.5988	0.7738
No log	53.0	106	0.6762	0.5214	0.6760	0.8222
No log	54.0	108	0.5904	0.5655	0.5901	0.7682
No log	55.0	110	0.5785	0.5449	0.5782	0.7604
No log	56.0	112	0.6117	0.5107	0.6115	0.7820
No log	57.0	114	0.6318	0.5095	0.6316	0.7947
No log	58.0	116	0.6379	0.5352	0.6375	0.7984

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_sp010_lw060_fold2

Trial3BERT_AugV8_k1_task1_organization_sp010_lw060_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_sp010_lw060_fold2