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	16.3273	0.0	16.3273	4.0407
No log	2.0	4	15.3898	0.0	15.3898	3.9230
No log	3.0	6	13.7783	0.0009	13.7783	3.7119
No log	4.0	8	10.9543	0.0142	10.9543	3.3097
No log	5.0	10	9.1854	0.0054	9.1854	3.0307
No log	6.0	12	7.5857	0.0	7.5857	2.7542
No log	7.0	14	5.9074	0.0656	5.9074	2.4305
No log	8.0	16	4.4102	0.0095	4.4102	2.1000
No log	9.0	18	3.4249	0.0077	3.4249	1.8507
No log	10.0	20	2.4519	0.0963	2.4519	1.5659
No log	11.0	22	1.6431	0.0453	1.6431	1.2818
No log	12.0	24	1.0374	0.0316	1.0374	1.0186
No log	13.0	26	0.8210	0.3872	0.8210	0.9061
No log	14.0	28	0.7327	0.2203	0.7327	0.8560
No log	15.0	30	0.7953	0.1124	0.7953	0.8918
No log	16.0	32	0.7808	0.1169	0.7808	0.8836
No log	17.0	34	0.7728	0.1883	0.7728	0.8791
No log	18.0	36	1.0646	0.2861	1.0646	1.0318
No log	19.0	38	1.1672	0.2581	1.1672	1.0804
No log	20.0	40	0.6491	0.4700	0.6491	0.8056
No log	21.0	42	0.5860	0.5205	0.5860	0.7655
No log	22.0	44	1.0478	0.4445	1.0478	1.0236
No log	23.0	46	0.8840	0.5008	0.8840	0.9402
No log	24.0	48	0.9312	0.4974	0.9312	0.9650
No log	25.0	50	1.2604	0.4307	1.2604	1.1227
No log	26.0	52	0.6954	0.5912	0.6954	0.8339
No log	27.0	54	0.8359	0.5608	0.8359	0.9143
No log	28.0	56	0.6231	0.6133	0.6231	0.7894
No log	29.0	58	0.8627	0.5016	0.8627	0.9288
No log	30.0	60	0.6895	0.5724	0.6895	0.8304
No log	31.0	62	0.7056	0.6052	0.7056	0.8400
No log	32.0	64	0.6004	0.6349	0.6004	0.7748
No log	33.0	66	0.6613	0.5604	0.6613	0.8132
No log	34.0	68	0.5771	0.6316	0.5771	0.7597
No log	35.0	70	0.7935	0.5704	0.7935	0.8908
No log	36.0	72	0.6808	0.5921	0.6808	0.8251
No log	37.0	74	0.6776	0.5665	0.6776	0.8232
No log	38.0	76	0.6887	0.5993	0.6887	0.8299
No log	39.0	78	0.8102	0.5874	0.8102	0.9001
No log	40.0	80	0.7937	0.6027	0.7937	0.8909
No log	41.0	82	0.7707	0.6107	0.7707	0.8779
No log	42.0	84	0.8642	0.5577	0.8642	0.9296
No log	43.0	86	0.7403	0.5893	0.7403	0.8604
No log	44.0	88	0.6800	0.5876	0.6800	0.8246
No log	45.0	90	0.6993	0.5714	0.6993	0.8362
No log	46.0	92	0.7331	0.6011	0.7331	0.8562
No log	47.0	94	0.7913	0.5839	0.7913	0.8896
No log	48.0	96	0.7121	0.5886	0.7121	0.8439
No log	49.0	98	0.7146	0.5927	0.7146	0.8453
No log	50.0	100	0.7682	0.5984	0.7682	0.8765
No log	51.0	102	0.8059	0.5854	0.8059	0.8977
No log	52.0	104	0.6597	0.6280	0.6597	0.8122

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version5ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

Version5ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version5ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0