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	5.0934	0.0078	5.0937	2.2569
No log	2.0	16	2.3414	0.0956	2.3418	1.5303
No log	3.0	24	1.9782	0.0280	1.9787	1.4067
No log	4.0	32	1.4139	0.0	1.4145	1.1893
No log	5.0	40	1.9936	0.0555	1.9939	1.4121
No log	6.0	48	1.1988	0.0	1.1994	1.0952
No log	7.0	56	1.3614	0.0241	1.3618	1.1670
No log	8.0	64	1.2276	0.1114	1.2279	1.1081
No log	9.0	72	1.8615	0.1786	1.8618	1.3645
No log	10.0	80	1.7131	0.2062	1.7131	1.3088
No log	11.0	88	1.2766	0.2309	1.2762	1.1297
No log	12.0	96	1.1497	0.2750	1.1489	1.0719
No log	13.0	104	1.4811	0.2381	1.4798	1.2165
No log	14.0	112	1.0804	0.2914	1.0796	1.0390
No log	15.0	120	1.5812	0.1820	1.5807	1.2573
No log	16.0	128	1.1914	0.2942	1.1910	1.0913
No log	17.0	136	1.6180	0.2197	1.6178	1.2719
No log	18.0	144	1.4053	0.2255	1.4050	1.1853
No log	19.0	152	0.9945	0.3196	0.9939	0.9969
No log	20.0	160	0.9634	0.2972	0.9629	0.9813
No log	21.0	168	1.0740	0.2926	1.0736	1.0361
No log	22.0	176	1.3376	0.1942	1.3375	1.1565
No log	23.0	184	1.0872	0.2692	1.0868	1.0425
No log	24.0	192	1.1822	0.2575	1.1820	1.0872
No log	25.0	200	0.8757	0.3633	0.8752	0.9355
No log	26.0	208	0.8194	0.3337	0.8190	0.9050
No log	27.0	216	0.8688	0.3281	0.8684	0.9319
No log	28.0	224	1.0179	0.3042	1.0173	1.0086
No log	29.0	232	0.9038	0.3596	0.9031	0.9503
No log	30.0	240	0.8858	0.3355	0.8853	0.9409
No log	31.0	248	1.0030	0.2903	1.0026	1.0013
No log	32.0	256	0.9533	0.3141	0.9528	0.9761
No log	33.0	264	0.9728	0.2881	0.9721	0.9860
No log	34.0	272	0.9806	0.3013	0.9801	0.9900
No log	35.0	280	1.0104	0.3074	1.0099	1.0049
No log	36.0	288	1.1264	0.2843	1.1260	1.0611
No log	37.0	296	1.2890	0.2034	1.2885	1.1351
No log	38.0	304	1.3297	0.1954	1.3293	1.1529
No log	39.0	312	1.3314	0.2103	1.3309	1.1536
No log	40.0	320	0.9649	0.3120	0.9645	0.9821
No log	41.0	328	0.9568	0.3442	0.9563	0.9779
No log	42.0	336	1.0633	0.2703	1.0629	1.0310
No log	43.0	344	1.1943	0.2476	1.1938	1.0926
No log	44.0	352	1.0904	0.2574	1.0900	1.0440
No log	45.0	360	1.1113	0.2655	1.1109	1.0540

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV11_k10_task1_organization_k10_k10_fold2

ASAP_FineTuningBERT_AugV11_k10_task1_organization_k10_k10_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV11_k10_task1_organization_k10_k10_fold2