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	6	6.8581	0.0	6.8581	2.6188
No log	2.0	12	4.3691	0.0039	4.3691	2.0902
No log	3.0	18	2.2419	0.0978	2.2419	1.4973
No log	4.0	24	1.5660	0.0316	1.5660	1.2514
No log	5.0	30	1.5485	0.0812	1.5485	1.2444
No log	6.0	36	1.1205	0.0548	1.1205	1.0585
No log	7.0	42	0.8572	0.2370	0.8572	0.9258
No log	8.0	48	1.2127	0.2241	1.2127	1.1012
No log	9.0	54	1.5191	0.1836	1.5191	1.2325
No log	10.0	60	0.6513	0.3780	0.6513	0.8070
No log	11.0	66	0.6865	0.3707	0.6865	0.8285
No log	12.0	72	1.3248	0.2663	1.3248	1.1510
No log	13.0	78	0.8770	0.4012	0.8770	0.9365
No log	14.0	84	1.0134	0.3616	1.0134	1.0067
No log	15.0	90	0.8064	0.4479	0.8064	0.8980
No log	16.0	96	0.7892	0.4473	0.7892	0.8884
No log	17.0	102	0.8242	0.4132	0.8242	0.9079
No log	18.0	108	0.7055	0.4843	0.7055	0.8399
No log	19.0	114	0.9884	0.3906	0.9884	0.9942
No log	20.0	120	0.9523	0.3417	0.9523	0.9759
No log	21.0	126	1.0356	0.2897	1.0356	1.0176
No log	22.0	132	0.7841	0.4533	0.7841	0.8855
No log	23.0	138	0.7382	0.4769	0.7382	0.8592
No log	24.0	144	0.9644	0.3585	0.9644	0.9820
No log	25.0	150	0.9230	0.3518	0.9230	0.9607
No log	26.0	156	0.7085	0.5069	0.7085	0.8417
No log	27.0	162	0.7725	0.4805	0.7725	0.8789
No log	28.0	168	0.6923	0.4770	0.6923	0.8320
No log	29.0	174	0.7792	0.4359	0.7792	0.8827
No log	30.0	180	0.7854	0.4295	0.7854	0.8862
No log	31.0	186	0.7351	0.4569	0.7351	0.8574
No log	32.0	192	0.7243	0.4641	0.7243	0.8511
No log	33.0	198	0.8095	0.4408	0.8095	0.8997
No log	34.0	204	0.6788	0.4955	0.6788	0.8239
No log	35.0	210	0.9401	0.3507	0.9401	0.9696
No log	36.0	216	0.9321	0.3338	0.9321	0.9655
No log	37.0	222	0.7585	0.4256	0.7585	0.8709
No log	38.0	228	0.7147	0.4616	0.7147	0.8454
No log	39.0	234	0.8298	0.4555	0.8298	0.9109
No log	40.0	240	0.7739	0.4140	0.7739	0.8797
No log	41.0	246	0.8202	0.4151	0.8202	0.9056
No log	42.0	252	0.7842	0.4332	0.7842	0.8855
No log	43.0	258	0.7672	0.4487	0.7672	0.8759
No log	44.0	264	0.7469	0.4287	0.7469	0.8642
No log	45.0	270	0.7405	0.4620	0.7405	0.8606
No log	46.0	276	0.6858	0.4669	0.6858	0.8281

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version2ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_k7_fold0

Version2ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_k7_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version2ASAP_FineTuningBERT_AugV8_k7_task1_organization_k7_k7_fold0