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	4	7.4760	0.0	7.4759	2.7342
No log	2.0	8	4.2494	0.0039	4.2498	2.0615
No log	3.0	12	2.7486	0.0	2.7491	1.6580
No log	4.0	16	1.6017	0.0280	1.6021	1.2657
No log	5.0	20	1.2906	0.0107	1.2911	1.1363
No log	6.0	24	1.2860	0.0	1.2865	1.1342
No log	7.0	28	1.0990	0.0136	1.0994	1.0485
No log	8.0	32	1.6387	-0.0500	1.6389	1.2802
No log	9.0	36	0.8978	0.1204	0.8981	0.9477
No log	10.0	40	1.2292	0.1022	1.2293	1.1088
No log	11.0	44	1.2697	0.0719	1.2698	1.1269
No log	12.0	48	0.7805	0.2764	0.7806	0.8835
No log	13.0	52	1.1398	0.0164	1.1398	1.0676
No log	14.0	56	1.2959	-0.0335	1.2957	1.1383
No log	15.0	60	0.8350	0.1738	0.8349	0.9137
No log	16.0	64	1.1318	0.1225	1.1314	1.0637
No log	17.0	68	1.2056	0.1572	1.2050	1.0977
No log	18.0	72	0.7985	0.3324	0.7984	0.8935
No log	19.0	76	0.9066	0.3074	0.9069	0.9523
No log	20.0	80	1.0416	0.1907	1.0416	1.0206
No log	21.0	84	0.7704	0.4653	0.7704	0.8777
No log	22.0	88	1.3253	0.1896	1.3249	1.1510
No log	23.0	92	0.6966	0.5036	0.6962	0.8344
No log	24.0	96	1.0701	0.2564	1.0697	1.0343
No log	25.0	100	0.9603	0.2680	0.9604	0.9800
No log	26.0	104	0.9985	0.1897	0.9984	0.9992
No log	27.0	108	1.0387	0.1902	1.0385	1.0190
No log	28.0	112	1.0030	0.2215	1.0030	1.0015
No log	29.0	116	1.4929	0.0977	1.4925	1.2217
No log	30.0	120	0.8239	0.3434	0.8237	0.9076
No log	31.0	124	1.2887	0.1464	1.2882	1.1350
No log	32.0	128	0.9219	0.2763	0.9216	0.9600
No log	33.0	132	1.1002	0.1774	1.0999	1.0488
No log	34.0	136	1.1427	0.1220	1.1428	1.0690
No log	35.0	140	0.9377	0.2526	0.9378	0.9684
No log	36.0	144	1.0713	0.1605	1.0715	1.0351
No log	37.0	148	1.0162	0.2055	1.0161	1.0080
No log	38.0	152	0.9860	0.2486	0.9858	0.9929
No log	39.0	156	0.8842	0.3193	0.8840	0.9402
No log	40.0	160	1.0114	0.2484	1.0112	1.0056
No log	41.0	164	1.0885	0.1837	1.0884	1.0433
No log	42.0	168	1.0398	0.1446	1.0399	1.0198
No log	43.0	172	0.9929	0.2375	0.9928	0.9964

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV11_k5_task1_organization_k5_k5_fold2

ASAP_FineTuningBERT_AugV11_k5_task1_organization_k5_k5_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV11_k5_task1_organization_k5_k5_fold2