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	4	10.3445	0.0	10.3445	3.2163
No log	2.0	8	8.0201	0.0	8.0201	2.8320
No log	3.0	12	5.7758	0.0291	5.7758	2.4033
No log	4.0	16	3.6093	0.0	3.6093	1.8998
No log	5.0	20	1.7676	0.0566	1.7676	1.3295
No log	6.0	24	1.5400	0.0988	1.5400	1.2410
No log	7.0	28	1.5926	0.0986	1.5926	1.2620
No log	8.0	32	1.1125	0.0566	1.1125	1.0548
No log	9.0	36	1.5164	0.1036	1.5164	1.2314
No log	10.0	40	1.4271	0.1403	1.4271	1.1946
No log	11.0	44	1.0922	0.3023	1.0922	1.0451
No log	12.0	48	1.7008	0.2248	1.7008	1.3041
No log	13.0	52	1.2754	0.2319	1.2754	1.1293
No log	14.0	56	1.0867	0.2635	1.0867	1.0424
No log	15.0	60	0.7877	0.3857	0.7877	0.8875
No log	16.0	64	0.7448	0.3831	0.7448	0.8630
No log	17.0	68	0.8136	0.3927	0.8136	0.9020
No log	18.0	72	0.8321	0.3974	0.8321	0.9122
No log	19.0	76	0.7806	0.4335	0.7806	0.8835
No log	20.0	80	0.7913	0.4089	0.7913	0.8895
No log	21.0	84	0.8274	0.4741	0.8274	0.9096
No log	22.0	88	0.7679	0.4957	0.7679	0.8763
No log	23.0	92	0.7153	0.5252	0.7153	0.8458
No log	24.0	96	0.7829	0.5021	0.7829	0.8848
No log	25.0	100	0.7443	0.5147	0.7443	0.8627
No log	26.0	104	0.7001	0.5030	0.7001	0.8367
No log	27.0	108	0.8490	0.4223	0.8490	0.9214
No log	28.0	112	0.7907	0.4936	0.7907	0.8892
No log	29.0	116	0.7907	0.4656	0.7907	0.8892
No log	30.0	120	0.8563	0.4722	0.8563	0.9254
No log	31.0	124	0.7875	0.4802	0.7875	0.8874
No log	32.0	128	0.7727	0.4949	0.7727	0.8790
No log	33.0	132	0.7594	0.4772	0.7594	0.8714
No log	34.0	136	0.8342	0.4823	0.8342	0.9134
No log	35.0	140	0.9018	0.4507	0.9018	0.9496
No log	36.0	144	0.8363	0.4763	0.8363	0.9145
No log	37.0	148	0.7759	0.4947	0.7759	0.8808
No log	38.0	152	0.8018	0.5075	0.8018	0.8954
No log	39.0	156	0.8602	0.4681	0.8602	0.9275
No log	40.0	160	0.8379	0.4699	0.8379	0.9154
No log	41.0	164	0.7646	0.4919	0.7646	0.8744
No log	42.0	168	0.8308	0.4476	0.8308	0.9115
No log	43.0	172	0.7928	0.4524	0.7928	0.8904

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12NewTestASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold4

Version12NewTestASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12NewTestASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold4