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	3	10.8731	0.0212	10.8715	3.2972
No log	2.0	6	7.1590	0.0	7.1577	2.6754
No log	3.0	9	5.0278	0.0231	5.0267	2.2420
No log	4.0	12	3.2826	0.0	3.2816	1.8115
No log	5.0	15	2.2527	0.0845	2.2518	1.5006
No log	6.0	18	1.6982	0.0401	1.6975	1.3029
No log	7.0	21	1.2307	0.0102	1.2302	1.1091
No log	8.0	24	0.9755	0.0147	0.9750	0.9874
No log	9.0	27	0.9082	0.1603	0.9077	0.9528
No log	10.0	30	1.0634	0.0246	1.0628	1.0309
No log	11.0	33	1.1871	0.0522	1.1865	1.0893
No log	12.0	36	0.8327	0.3499	0.8323	0.9123
No log	13.0	39	0.8405	0.3093	0.8402	0.9166
No log	14.0	42	0.8153	0.3699	0.8154	0.9030
No log	15.0	45	0.7220	0.4414	0.7225	0.8500
No log	16.0	48	0.7379	0.3951	0.7387	0.8595
No log	17.0	51	0.6366	0.4412	0.6372	0.7982
No log	18.0	54	0.6836	0.4445	0.6846	0.8274
No log	19.0	57	0.6410	0.4604	0.6418	0.8011
No log	20.0	60	0.9416	0.3961	0.9427	0.9709
No log	21.0	63	0.6885	0.4779	0.6896	0.8304
No log	22.0	66	1.0113	0.3936	1.0128	1.0064
No log	23.0	69	0.7933	0.4486	0.7943	0.8912
No log	24.0	72	0.7713	0.4156	0.7718	0.8785
No log	25.0	75	1.2071	0.2935	1.2075	1.0989
No log	26.0	78	0.7577	0.4337	0.7582	0.8707
No log	27.0	81	0.8966	0.3842	0.8970	0.9471
No log	28.0	84	0.7872	0.4343	0.7877	0.8875
No log	29.0	87	0.7579	0.4459	0.7583	0.8708
No log	30.0	90	1.0432	0.3581	1.0438	1.0217
No log	31.0	93	0.7346	0.4858	0.7352	0.8574
No log	32.0	96	0.7871	0.4476	0.7876	0.8875
No log	33.0	99	0.7108	0.4837	0.7112	0.8434
No log	34.0	102	0.9913	0.3915	0.9918	0.9959
No log	35.0	105	0.7390	0.4583	0.7396	0.8600
No log	36.0	108	1.0036	0.3486	1.0040	1.0020
No log	37.0	111	0.6742	0.5029	0.6747	0.8214
No log	38.0	114	1.0077	0.3297	1.0080	1.0040
No log	39.0	117	0.7955	0.4296	0.7959	0.8921
No log	40.0	120	0.7406	0.4814	0.7412	0.8609
No log	41.0	123	1.1109	0.3147	1.1112	1.0542
No log	42.0	126	1.1925	0.3358	1.1927	1.0921
No log	43.0	129	0.6560	0.5122	0.6565	0.8102
No log	44.0	132	0.6950	0.4901	0.6955	0.8339
No log	45.0	135	1.2797	0.3183	1.2799	1.1313
No log	46.0	138	0.7418	0.4396	0.7422	0.8615
No log	47.0	141	0.6887	0.4747	0.6891	0.8301
No log	48.0	144	1.2308	0.2784	1.2310	1.1095
No log	49.0	147	0.8439	0.3770	0.8442	0.9188
No log	50.0	150	0.8565	0.3590	0.8566	0.9255
No log	51.0	153	0.8170	0.3710	0.8172	0.9040
No log	52.0	156	1.0053	0.3226	1.0055	1.0027
No log	53.0	159	0.7929	0.4111	0.7932	0.8906
No log	54.0	162	0.7745	0.4095	0.7748	0.8802
No log	55.0	165	1.0011	0.3298	1.0013	1.0007
No log	56.0	168	0.6718	0.4797	0.6722	0.8199
No log	57.0	171	1.0093	0.3577	1.0097	1.0048
No log	58.0	174	0.9768	0.3600	0.9772	0.9885

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Trial2BERT_AugV8_k3_task1_organization_sp010_lw050_fold3

Trial2BERT_AugV8_k3_task1_organization_sp010_lw050_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial2BERT_AugV8_k3_task1_organization_sp010_lw050_fold3