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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	9.5267	0.0018	9.5267	3.0865
No log	2.0	4	7.9182	0.0018	7.9182	2.8139
No log	3.0	6	6.3918	0.0	6.3918	2.5282
No log	4.0	8	5.0953	0.0237	5.0953	2.2573
No log	5.0	10	4.1485	0.0118	4.1485	2.0368
No log	6.0	12	3.5302	0.0079	3.5302	1.8789
No log	7.0	14	2.7113	0.0040	2.7113	1.6466
No log	8.0	16	2.2991	0.1749	2.2991	1.5163
No log	9.0	18	2.0877	0.1883	2.0877	1.4449
No log	10.0	20	1.5932	0.0771	1.5932	1.2622
No log	11.0	22	1.3142	0.0420	1.3142	1.1464
No log	12.0	24	1.2472	0.0930	1.2472	1.1168
No log	13.0	26	1.0362	0.0930	1.0362	1.0179
No log	14.0	28	0.9395	0.1055	0.9395	0.9693
No log	15.0	30	1.0182	0.1881	1.0182	1.0090
No log	16.0	32	1.0876	0.2403	1.0876	1.0429
No log	17.0	34	0.8094	0.4788	0.8094	0.8997
No log	18.0	36	0.8182	0.4858	0.8182	0.9046
No log	19.0	38	0.6664	0.5345	0.6664	0.8163
No log	20.0	40	0.6379	0.5520	0.6379	0.7987
No log	21.0	42	0.5766	0.5561	0.5766	0.7593
No log	22.0	44	0.5309	0.5373	0.5309	0.7286
No log	23.0	46	0.6369	0.5715	0.6369	0.7981
No log	24.0	48	0.6110	0.5888	0.6110	0.7817
No log	25.0	50	0.5074	0.5194	0.5074	0.7123
No log	26.0	52	0.5484	0.5377	0.5484	0.7406
No log	27.0	54	0.5740	0.6073	0.5740	0.7576
No log	28.0	56	0.6846	0.5397	0.6846	0.8274
No log	29.0	58	0.5196	0.6503	0.5196	0.7208
No log	30.0	60	0.6976	0.5585	0.6976	0.8352
No log	31.0	62	0.5661	0.6334	0.5661	0.7524
No log	32.0	64	0.5611	0.6096	0.5611	0.7491
No log	33.0	66	0.5906	0.5891	0.5906	0.7685
No log	34.0	68	0.5619	0.6410	0.5619	0.7496
No log	35.0	70	0.6655	0.5964	0.6655	0.8158
No log	36.0	72	0.5447	0.6379	0.5447	0.7380
No log	37.0	74	0.6056	0.5944	0.6056	0.7782
No log	38.0	76	0.5811	0.6374	0.5811	0.7623
No log	39.0	78	0.6136	0.6216	0.6136	0.7833
No log	40.0	80	0.6146	0.5649	0.6146	0.7840
No log	41.0	82	0.5891	0.5669	0.5891	0.7675
No log	42.0	84	0.5718	0.6361	0.5718	0.7562
No log	43.0	86	0.6039	0.6186	0.6039	0.7771
No log	44.0	88	0.5591	0.6302	0.5591	0.7477
No log	45.0	90	0.6362	0.6163	0.6362	0.7976
No log	46.0	92	0.6182	0.6307	0.6182	0.7862
No log	47.0	94	0.5752	0.6159	0.5752	0.7584
No log	48.0	96	0.5763	0.6187	0.5763	0.7591
No log	49.0	98	0.5861	0.6465	0.5861	0.7656

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_changed_semanticV2_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4

ASAP_changed_semanticV2_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_changed_semanticV2_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4