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	7.6041	0.0	7.6041	2.7576
No log	2.0	8	5.9311	0.0236	5.9311	2.4354
No log	3.0	12	4.2221	0.0039	4.2221	2.0548
No log	4.0	16	2.6907	0.0	2.6907	1.6403
No log	5.0	20	1.7854	0.0316	1.7854	1.3362
No log	6.0	24	1.6285	0.0484	1.6285	1.2761
No log	7.0	28	1.2259	0.0316	1.2259	1.1072
No log	8.0	32	1.3836	0.0825	1.3836	1.1763
No log	9.0	36	1.2649	0.1430	1.2649	1.1247
No log	10.0	40	1.1223	0.2184	1.1223	1.0594
No log	11.0	44	0.8111	0.3561	0.8111	0.9006
No log	12.0	48	1.1692	0.2785	1.1692	1.0813
No log	13.0	52	0.6345	0.3695	0.6345	0.7965
No log	14.0	56	0.9785	0.3362	0.9785	0.9892
No log	15.0	60	0.6251	0.4427	0.6251	0.7906
No log	16.0	64	0.7106	0.4905	0.7106	0.8430
No log	17.0	68	0.8046	0.4370	0.8046	0.8970
No log	18.0	72	0.6885	0.5073	0.6885	0.8297
No log	19.0	76	0.8100	0.4554	0.8100	0.9000
No log	20.0	80	0.7800	0.4333	0.7800	0.8832
No log	21.0	84	0.6875	0.4906	0.6875	0.8291
No log	22.0	88	0.7448	0.4569	0.7448	0.8630
No log	23.0	92	0.8046	0.4443	0.8046	0.8970
No log	24.0	96	0.6670	0.5151	0.6670	0.8167
No log	25.0	100	0.7694	0.4321	0.7694	0.8771
No log	26.0	104	0.7666	0.4515	0.7666	0.8756
No log	27.0	108	0.6832	0.5375	0.6832	0.8265
No log	28.0	112	0.7324	0.4695	0.7324	0.8558
No log	29.0	116	0.7361	0.4636	0.7361	0.8579
No log	30.0	120	0.6848	0.5216	0.6848	0.8276
No log	31.0	124	0.7741	0.4093	0.7741	0.8798
No log	32.0	128	0.7293	0.4648	0.7293	0.8540
No log	33.0	132	0.7498	0.4655	0.7498	0.8659
No log	34.0	136	0.7007	0.4612	0.7007	0.8371
No log	35.0	140	0.7346	0.4980	0.7346	0.8571
No log	36.0	144	0.7129	0.4617	0.7129	0.8443
No log	37.0	148	0.6956	0.4935	0.6956	0.8340
No log	38.0	152	0.7281	0.5328	0.7281	0.8533
No log	39.0	156	0.6858	0.4953	0.6858	0.8281
No log	40.0	160	0.6978	0.5209	0.6978	0.8354
No log	41.0	164	0.7319	0.5255	0.7319	0.8555
No log	42.0	168	0.7595	0.4446	0.7595	0.8715
No log	43.0	172	0.6955	0.4931	0.6955	0.8339
No log	44.0	176	0.6938	0.5121	0.6938	0.8329
No log	45.0	180	0.6857	0.4902	0.6857	0.8281
No log	46.0	184	0.7001	0.4541	0.7001	0.8367
No log	47.0	188	0.7584	0.4334	0.7584	0.8709

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_fold0

ASAP_FineTuningBERT_AugV11_k5_task1_organization_k5_k5_fold0

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_fold0