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	13.0873	0.0	13.0873	3.6176
No log	2.0	4	11.2761	-0.0156	11.2763	3.3580
No log	3.0	6	10.1188	0.0	10.1191	3.1811
No log	4.0	8	8.5348	0.0	8.5354	2.9215
No log	5.0	10	7.2636	0.0	7.2640	2.6952
No log	6.0	12	6.3508	0.0052	6.3513	2.5202
No log	7.0	14	5.3847	0.0046	5.3851	2.3206
No log	8.0	16	4.2174	0.0039	4.2180	2.0538
No log	9.0	18	3.0089	0.0039	3.0095	1.7348
No log	10.0	20	2.4765	0.0564	2.4771	1.5739
No log	11.0	22	2.0093	0.0830	2.0099	1.4177
No log	12.0	24	1.8745	0.0542	1.8751	1.3693
No log	13.0	26	1.5129	0.0213	1.5134	1.2302
No log	14.0	28	1.3854	0.0361	1.3858	1.1772
No log	15.0	30	1.0392	0.0213	1.0395	1.0196
No log	16.0	32	1.1683	0.0195	1.1689	1.0811
No log	17.0	34	1.4354	0.0280	1.4359	1.1983
No log	18.0	36	1.1525	0.0166	1.1531	1.0738
No log	19.0	38	0.7874	0.2709	0.7879	0.8877
No log	20.0	40	0.8756	0.0946	0.8761	0.9360
No log	21.0	42	1.2277	0.0551	1.2283	1.1083
No log	22.0	44	0.9952	0.1104	0.9957	0.9978
No log	23.0	46	0.8108	0.3387	0.8111	0.9006
No log	24.0	48	0.9165	0.2990	0.9170	0.9576
No log	25.0	50	1.2023	0.1935	1.2030	1.0968
No log	26.0	52	1.0450	0.2228	1.0459	1.0227
No log	27.0	54	1.2098	0.2215	1.2108	1.1004
No log	28.0	56	1.2579	0.2768	1.2587	1.1219
No log	29.0	58	0.8159	0.4542	0.8165	0.9036
No log	30.0	60	1.0618	0.3015	1.0628	1.0309
No log	31.0	62	1.2805	0.1947	1.2818	1.1322
No log	32.0	64	0.7875	0.4147	0.7884	0.8879
No log	33.0	66	0.5916	0.5206	0.5918	0.7693
No log	34.0	68	0.7445	0.4350	0.7451	0.8632
No log	35.0	70	1.1240	0.2514	1.1251	1.0607
No log	36.0	72	0.8021	0.3817	0.8031	0.8962
No log	37.0	74	0.7899	0.3327	0.7904	0.8891
No log	38.0	76	0.8468	0.3850	0.8480	0.9209
No log	39.0	78	0.9146	0.3667	0.9159	0.9570
No log	40.0	80	0.8091	0.4487	0.8100	0.9000
No log	41.0	82	1.0071	0.3417	1.0085	1.0043
No log	42.0	84	1.2039	0.2716	1.2057	1.0980
No log	43.0	86	1.0710	0.2896	1.0727	1.0357
No log	44.0	88	0.9033	0.4120	0.9045	0.9511
No log	45.0	90	1.0120	0.2986	1.0133	1.0066
No log	46.0	92	1.3262	0.1960	1.3272	1.1521
No log	47.0	94	0.8587	0.3938	0.8595	0.9271
No log	48.0	96	0.7788	0.4634	0.7796	0.8829
No log	49.0	98	0.9160	0.3918	0.9170	0.9576
No log	50.0	100	1.5695	0.1670	1.5705	1.2532
No log	51.0	102	1.3420	0.2220	1.3434	1.1590
No log	52.0	104	0.9281	0.4139	0.9295	0.9641
No log	53.0	106	0.9169	0.4009	0.9183	0.9583

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV11_k1_task1_organization_k1_k1_fold2

ASAP_FineTuningBERT_AugV11_k1_task1_organization_k1_k1_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV11_k1_task1_organization_k1_k1_fold2