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	3	9.0709	0.0	9.0692	3.0115
No log	2.0	6	7.0726	0.0	7.0714	2.6592
No log	3.0	9	4.4940	0.0103	4.4927	2.1196
No log	4.0	12	3.5629	0.0	3.5621	1.8873
No log	5.0	15	2.1039	0.1236	2.1032	1.4502
No log	6.0	18	1.4017	0.0302	1.4012	1.1837
No log	7.0	21	1.1010	0.0302	1.1006	1.0491
No log	8.0	24	1.3092	0.0401	1.3088	1.1440
No log	9.0	27	1.2646	0.0764	1.2643	1.1244
No log	10.0	30	0.9638	0.1779	0.9636	0.9816
No log	11.0	33	1.0327	0.2366	1.0326	1.0162
No log	12.0	36	0.8563	0.3436	0.8561	0.9253
No log	13.0	39	0.7624	0.4271	0.7625	0.8732
No log	14.0	42	1.1205	0.3425	1.1205	1.0586
No log	15.0	45	0.7320	0.4575	0.7322	0.8557
No log	16.0	48	0.9132	0.3874	0.9135	0.9558
No log	17.0	51	0.7952	0.4216	0.7956	0.8919
No log	18.0	54	0.9094	0.4339	0.9099	0.9539
No log	19.0	57	0.8570	0.4717	0.8578	0.9262
No log	20.0	60	1.2533	0.3586	1.2541	1.1199
No log	21.0	63	0.8616	0.4483	0.8624	0.9286
No log	22.0	66	0.8660	0.4351	0.8667	0.9310
No log	23.0	69	0.7763	0.4742	0.7770	0.8815
No log	24.0	72	1.1124	0.3850	1.1130	1.0550
No log	25.0	75	0.8086	0.4915	0.8093	0.8996
No log	26.0	78	1.1994	0.3595	1.2000	1.0955
No log	27.0	81	0.8483	0.4487	0.8489	0.9214
No log	28.0	84	0.9288	0.4184	0.9293	0.9640
No log	29.0	87	0.8203	0.4529	0.8206	0.9059
No log	30.0	90	0.9340	0.4386	0.9344	0.9666
No log	31.0	93	0.8441	0.4734	0.8445	0.9190
No log	32.0	96	0.9143	0.4299	0.9148	0.9565
No log	33.0	99	0.8530	0.4155	0.8536	0.9239
No log	34.0	102	1.0436	0.3418	1.0443	1.0219
No log	35.0	105	0.9041	0.4038	0.9047	0.9512
No log	36.0	108	0.9940	0.3909	0.9945	0.9972
No log	37.0	111	0.8666	0.4494	0.8670	0.9311
No log	38.0	114	0.9585	0.4057	0.9589	0.9793
No log	39.0	117	0.8634	0.4701	0.8638	0.9294
No log	40.0	120	1.0094	0.3901	1.0098	1.0049
No log	41.0	123	0.8415	0.4776	0.8418	0.9175
No log	42.0	126	0.9574	0.4381	0.9578	0.9787
No log	43.0	129	0.8084	0.4731	0.8087	0.8993
No log	44.0	132	0.9270	0.4396	0.9273	0.9630
No log	45.0	135	0.7411	0.4781	0.7414	0.8611

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV6_k3_task1_organization_k3_k3_fold3

ASAP_FineTuningBERT_AugV6_k3_task1_organization_k3_k3_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k3_task1_organization_k3_k3_fold3