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	9.5370	0.0018	9.5352	3.0879
No log	2.0	4	8.0233	0.0	8.0215	2.8322
No log	3.0	6	6.4513	0.0003	6.4498	2.5396
No log	4.0	8	5.1219	0.0114	5.1205	2.2629
No log	5.0	10	4.0987	0.0038	4.0975	2.0242
No log	6.0	12	3.3150	0.0	3.3139	1.8204
No log	7.0	14	2.7664	0.0198	2.7656	1.6630
No log	8.0	16	2.0456	0.0361	2.0446	1.4299
No log	9.0	18	1.7053	0.0202	1.7044	1.3055
No log	10.0	20	1.4678	0.0202	1.4673	1.2113
No log	11.0	22	1.4514	0.0302	1.4509	1.2045
No log	12.0	24	1.3925	0.0302	1.3921	1.1799
No log	13.0	26	0.9251	0.1509	0.9249	0.9617
No log	14.0	28	0.9638	0.1349	0.9636	0.9816
No log	15.0	30	1.1819	0.0910	1.1819	1.0871
No log	16.0	32	1.4683	0.1398	1.4685	1.2118
No log	17.0	34	1.1261	0.2208	1.1267	1.0615
No log	18.0	36	0.7432	0.3787	0.7436	0.8623
No log	19.0	38	1.1084	0.2915	1.1094	1.0533
No log	20.0	40	1.2764	0.2742	1.2775	1.1303
No log	21.0	42	0.7276	0.3794	0.7285	0.8535
No log	22.0	44	0.7038	0.3910	0.7048	0.8395
No log	23.0	46	0.9764	0.3308	0.9775	0.9887
No log	24.0	48	0.8207	0.3855	0.8220	0.9066
No log	25.0	50	0.7085	0.4387	0.7099	0.8426
No log	26.0	52	1.0584	0.4244	1.0603	1.0297
No log	27.0	54	1.2803	0.3736	1.2823	1.1324
No log	28.0	56	1.0270	0.4423	1.0287	1.0142
No log	29.0	58	0.6999	0.5604	0.7012	0.8374
No log	30.0	60	0.7624	0.4683	0.7636	0.8738
No log	31.0	62	0.8812	0.4269	0.8823	0.9393
No log	32.0	64	0.6726	0.5282	0.6735	0.8207
No log	33.0	66	0.7049	0.5200	0.7059	0.8402
No log	34.0	68	0.7398	0.4418	0.7410	0.8608
No log	35.0	70	0.7360	0.5204	0.7370	0.8585
No log	36.0	72	0.7014	0.4854	0.7024	0.8381
No log	37.0	74	0.8079	0.4129	0.8090	0.8994
No log	38.0	76	0.7163	0.4289	0.7172	0.8469
No log	39.0	78	0.7584	0.4379	0.7594	0.8714
No log	40.0	80	0.9353	0.3929	0.9363	0.9676
No log	41.0	82	0.7429	0.4487	0.7440	0.8625
No log	42.0	84	0.7144	0.5074	0.7154	0.8458
No log	43.0	86	0.7956	0.4442	0.7969	0.8927
No log	44.0	88	0.7922	0.4443	0.7935	0.8908
No log	45.0	90	0.7676	0.5170	0.7686	0.8767
No log	46.0	92	0.8422	0.5163	0.8431	0.9182
No log	47.0	94	0.6864	0.5200	0.6875	0.8292
No log	48.0	96	0.9382	0.4175	0.9395	0.9693
No log	49.0	98	0.9193	0.4158	0.9205	0.9594

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV10_k1_task1_organization_k1_k1_fold3

ASAP_FineTuningBERT_AugV10_k1_task1_organization_k1_k1_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV10_k1_task1_organization_k1_k1_fold3