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	9.8403	0.0018	9.8403	3.1369
No log	2.0	6	7.4052	0.0018	7.4052	2.7213
No log	3.0	9	5.2067	0.0317	5.2067	2.2818
No log	4.0	12	3.5993	0.0040	3.5993	1.8972
No log	5.0	15	2.5945	0.0008	2.5945	1.6108
No log	6.0	18	1.8063	0.0878	1.8063	1.3440
No log	7.0	21	1.4531	0.0585	1.4531	1.2054
No log	8.0	24	1.1297	0.0522	1.1297	1.0629
No log	9.0	27	1.0688	0.0748	1.0688	1.0338
No log	10.0	30	0.8010	0.3502	0.8010	0.8950
No log	11.0	33	1.2834	0.2023	1.2834	1.1329
No log	12.0	36	0.6803	0.4940	0.6803	0.8248
No log	13.0	39	0.8846	0.4061	0.8846	0.9405
No log	14.0	42	0.6577	0.5066	0.6577	0.8110
No log	15.0	45	0.7053	0.4062	0.7053	0.8398
No log	16.0	48	0.6076	0.5228	0.6076	0.7795
No log	17.0	51	0.5767	0.5264	0.5767	0.7594
No log	18.0	54	0.7848	0.5132	0.7848	0.8859
No log	19.0	57	0.5305	0.5894	0.5305	0.7284
No log	20.0	60	0.7426	0.5081	0.7426	0.8618
No log	21.0	63	0.6089	0.5051	0.6089	0.7803
No log	22.0	66	0.5955	0.5563	0.5955	0.7717
No log	23.0	69	0.5812	0.5454	0.5812	0.7623
No log	24.0	72	0.5856	0.5237	0.5856	0.7652
No log	25.0	75	0.5793	0.5074	0.5793	0.7611
No log	26.0	78	0.5728	0.5479	0.5728	0.7569
No log	27.0	81	0.6287	0.5638	0.6287	0.7929
No log	28.0	84	0.7946	0.4772	0.7946	0.8914
No log	29.0	87	0.5610	0.6004	0.5610	0.7490
No log	30.0	90	0.5782	0.6119	0.5782	0.7604
No log	31.0	93	0.6385	0.5552	0.6385	0.7990
No log	32.0	96	0.7546	0.5333	0.7546	0.8687
No log	33.0	99	0.5931	0.6246	0.5931	0.7702
No log	34.0	102	0.5999	0.6068	0.5999	0.7745
No log	35.0	105	0.7081	0.5548	0.7081	0.8415
No log	36.0	108	0.6292	0.5609	0.6292	0.7932
No log	37.0	111	0.6097	0.5912	0.6097	0.7808
No log	38.0	114	0.6483	0.5828	0.6483	0.8052
No log	39.0	117	0.6704	0.5762	0.6704	0.8188
No log	40.0	120	0.6390	0.5995	0.6390	0.7994
No log	41.0	123	0.7037	0.5694	0.7037	0.8389
No log	42.0	126	0.7509	0.5227	0.7509	0.8666
No log	43.0	129	0.6088	0.6114	0.6088	0.7803
No log	44.0	132	0.8077	0.5483	0.8077	0.8987
No log	45.0	135	0.7036	0.5864	0.7036	0.8388
No log	46.0	138	0.8671	0.5535	0.8671	0.9312
No log	47.0	141	0.6385	0.6257	0.6385	0.7991
No log	48.0	144	0.7468	0.5869	0.7468	0.8642
No log	49.0	147	0.6389	0.6292	0.6389	0.7993
No log	50.0	150	0.8643	0.5668	0.8643	0.9297
No log	51.0	153	0.8231	0.5699	0.8231	0.9073
No log	52.0	156	0.9391	0.5318	0.9391	0.9691
No log	53.0	159	0.6921	0.5994	0.6921	0.8319
No log	54.0	162	0.7483	0.5808	0.7483	0.8650
No log	55.0	165	0.6709	0.6036	0.6709	0.8191
No log	56.0	168	0.7485	0.5815	0.7485	0.8651
No log	57.0	171	0.6794	0.6086	0.6794	0.8242
No log	58.0	174	0.6338	0.6185	0.6338	0.7961
No log	59.0	177	0.6796	0.5972	0.6796	0.8244
No log	60.0	180	0.6991	0.5909	0.6991	0.8361
No log	61.0	183	0.7844	0.5537	0.7844	0.8856
No log	62.0	186	0.6924	0.5969	0.6924	0.8321
No log	63.0	189	0.6694	0.6033	0.6694	0.8182
No log	64.0	192	0.6762	0.5917	0.6762	0.8223
No log	65.0	195	0.8882	0.5247	0.8882	0.9424
No log	66.0	198	0.8139	0.5597	0.8139	0.9022
No log	67.0	201	0.6747	0.5939	0.6747	0.8214
No log	68.0	204	0.5894	0.6179	0.5894	0.7677
No log	69.0	207	0.6197	0.6134	0.6197	0.7872
No log	70.0	210	0.6774	0.5933	0.6774	0.8231
No log	71.0	213	0.8151	0.5563	0.8151	0.9028
No log	72.0	216	0.8360	0.5504	0.8360	0.9143
No log	73.0	219	0.7732	0.5688	0.7732	0.8793
No log	74.0	222	0.6583	0.6160	0.6583	0.8114
No log	75.0	225	0.7019	0.5978	0.7019	0.8378
No log	76.0	228	0.6831	0.6191	0.6831	0.8265
No log	77.0	231	0.8104	0.5697	0.8104	0.9002
No log	78.0	234	0.7269	0.5851	0.7269	0.8526
No log	79.0	237	0.7346	0.5681	0.7346	0.8571

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version24NewTestASAP_FineTuningBERT_AugV24_k5_task1_organization_k5_k5_fold4

Version24NewTestASAP_FineTuningBERT_AugV24_k5_task1_organization_k5_k5_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version24NewTestASAP_FineTuningBERT_AugV24_k5_task1_organization_k5_k5_fold4