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	8	5.4656	0.0227	5.4643	2.3376
No log	2.0	16	2.0529	0.1027	2.0521	1.4325
No log	3.0	24	1.3178	0.0365	1.3172	1.1477
No log	4.0	32	2.1853	0.1586	2.1847	1.4781
No log	5.0	40	1.8094	0.0754	1.8088	1.3449
No log	6.0	48	1.4052	0.2012	1.4053	1.1854
No log	7.0	56	1.4055	0.2048	1.4058	1.1857
No log	8.0	64	0.7528	0.3338	0.7526	0.8675
No log	9.0	72	0.8762	0.3618	0.8765	0.9362
No log	10.0	80	1.0437	0.3786	1.0441	1.0218
No log	11.0	88	0.9536	0.4011	0.9539	0.9767
No log	12.0	96	0.8688	0.3882	0.8689	0.9321
No log	13.0	104	1.0006	0.3254	1.0004	1.0002
No log	14.0	112	1.0575	0.2838	1.0572	1.0282
No log	15.0	120	0.8394	0.4059	0.8393	0.9161
No log	16.0	128	0.7912	0.3934	0.7910	0.8894
No log	17.0	136	0.9887	0.3469	0.9885	0.9942
No log	18.0	144	0.7428	0.4327	0.7427	0.8618
No log	19.0	152	0.6856	0.4430	0.6855	0.8280
No log	20.0	160	1.1236	0.3413	1.1235	1.0600
No log	21.0	168	0.7526	0.4162	0.7525	0.8675
No log	22.0	176	0.7151	0.4407	0.7151	0.8456
No log	23.0	184	0.9819	0.3662	0.9819	0.9909
No log	24.0	192	0.6616	0.4689	0.6617	0.8134
No log	25.0	200	0.7528	0.4436	0.7529	0.8677
No log	26.0	208	0.7320	0.4660	0.7322	0.8557
No log	27.0	216	0.8828	0.4057	0.8828	0.9396
No log	28.0	224	0.6985	0.4494	0.6984	0.8357
No log	29.0	232	0.8334	0.4443	0.8334	0.9129
No log	30.0	240	0.6912	0.4627	0.6912	0.8314
No log	31.0	248	0.8702	0.4053	0.8702	0.9328
No log	32.0	256	0.6612	0.4732	0.6611	0.8131
No log	33.0	264	0.7757	0.4406	0.7758	0.8808
No log	34.0	272	0.8900	0.4066	0.8901	0.9434
No log	35.0	280	0.8444	0.3880	0.8444	0.9189
No log	36.0	288	0.6594	0.4495	0.6593	0.8120
No log	37.0	296	0.6660	0.4664	0.6660	0.8161
No log	38.0	304	0.8183	0.3836	0.8183	0.9046
No log	39.0	312	0.6994	0.4715	0.6994	0.8363
No log	40.0	320	0.7188	0.4582	0.7188	0.8478
No log	41.0	328	0.7023	0.4579	0.7023	0.8380
No log	42.0	336	0.7282	0.4490	0.7281	0.8533

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV7_k10_task1_organization_k10_k10_fold3

ASAP_FineTuningBERT_AugV7_k10_task1_organization_k10_k10_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV7_k10_task1_organization_k10_k10_fold3