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	7.5901	0.0	7.5873	2.7545
No log	2.0	8	5.4580	-0.0169	5.4559	2.3358
No log	3.0	12	3.0880	0.0	3.0862	1.7568
No log	4.0	16	1.9613	0.0515	1.9595	1.3998
No log	5.0	20	1.1982	0.0315	1.1967	1.0939
No log	6.0	24	1.1555	0.0211	1.1539	1.0742
No log	7.0	28	0.9726	0.0211	0.9712	0.9855
No log	8.0	32	1.3235	0.0921	1.3220	1.1498
No log	9.0	36	0.8049	0.3838	0.8036	0.8964
No log	10.0	40	1.0592	0.1567	1.0576	1.0284
No log	11.0	44	0.8809	0.3094	0.8793	0.9377
No log	12.0	48	0.6438	0.4143	0.6426	0.8016
No log	13.0	52	0.6684	0.4239	0.6670	0.8167
No log	14.0	56	0.5948	0.4526	0.5934	0.7703
No log	15.0	60	0.5747	0.5010	0.5736	0.7574
No log	16.0	64	0.7767	0.4027	0.7756	0.8807
No log	17.0	68	0.7400	0.5138	0.7384	0.8593
No log	18.0	72	0.7265	0.5298	0.7254	0.8517
No log	19.0	76	0.7137	0.5339	0.7120	0.8438
No log	20.0	80	0.7435	0.5341	0.7425	0.8617
No log	21.0	84	0.6576	0.5621	0.6565	0.8102
No log	22.0	88	0.7275	0.5301	0.7261	0.8521
No log	23.0	92	1.1678	0.3992	1.1670	1.0803
No log	24.0	96	0.7110	0.5228	0.7095	0.8423
No log	25.0	100	0.6379	0.5566	0.6369	0.7980
No log	26.0	104	0.6638	0.5199	0.6624	0.8139
No log	27.0	108	1.0560	0.4521	1.0552	1.0272
No log	28.0	112	0.8106	0.4620	0.8089	0.8994
No log	29.0	116	1.0110	0.4738	1.0103	1.0051
No log	30.0	120	0.6333	0.5648	0.6320	0.7950
No log	31.0	124	0.6069	0.6152	0.6059	0.7784
No log	32.0	128	0.6388	0.5346	0.6376	0.7985
No log	33.0	132	0.8682	0.4770	0.8673	0.9313
No log	34.0	136	0.6419	0.5346	0.6405	0.8003
No log	35.0	140	0.6956	0.5606	0.6946	0.8334
No log	36.0	144	0.6931	0.5695	0.6918	0.8317
No log	37.0	148	0.8148	0.5284	0.8136	0.9020
No log	38.0	152	0.8426	0.4821	0.8416	0.9174
No log	39.0	156	0.7346	0.5225	0.7334	0.8564
No log	40.0	160	0.8443	0.4744	0.8433	0.9183
No log	41.0	164	0.8251	0.4986	0.8239	0.9077

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV7_k4_task1_organization_k4_k4_fold1

ASAP_FineTuningBERT_AugV7_k4_task1_organization_k4_k4_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV7_k4_task1_organization_k4_k4_fold1