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	12	4.1810	0.0039	4.1810	2.0448
No log	2.0	24	1.1971	0.0316	1.1971	1.0941
No log	3.0	36	1.0630	0.0484	1.0630	1.0310
No log	4.0	48	1.0416	0.0890	1.0416	1.0206
No log	5.0	60	1.9811	0.1266	1.9811	1.4075
No log	6.0	72	0.9637	0.3082	0.9637	0.9817
No log	7.0	84	0.7330	0.4841	0.7330	0.8561
No log	8.0	96	1.4719	0.2603	1.4719	1.2132
No log	9.0	108	0.9220	0.4206	0.9220	0.9602
No log	10.0	120	0.8886	0.4073	0.8886	0.9426
No log	11.0	132	1.0742	0.3191	1.0742	1.0365
No log	12.0	144	0.7911	0.4108	0.7911	0.8895
No log	13.0	156	0.7996	0.4440	0.7996	0.8942
No log	14.0	168	0.7277	0.4093	0.7277	0.8531
No log	15.0	180	1.1380	0.3380	1.1380	1.0668
No log	16.0	192	0.8718	0.3633	0.8718	0.9337
No log	17.0	204	0.7786	0.4081	0.7786	0.8824
No log	18.0	216	0.7308	0.4414	0.7308	0.8549
No log	19.0	228	0.8720	0.4100	0.8720	0.9338
No log	20.0	240	0.9512	0.3837	0.9512	0.9753
No log	21.0	252	0.7312	0.4556	0.7312	0.8551
No log	22.0	264	0.6769	0.4442	0.6769	0.8228
No log	23.0	276	0.7028	0.4436	0.7028	0.8383
No log	24.0	288	0.8036	0.4204	0.8036	0.8964
No log	25.0	300	0.6696	0.4861	0.6696	0.8183
No log	26.0	312	0.7789	0.4261	0.7789	0.8826
No log	27.0	324	0.7577	0.4754	0.7577	0.8705
No log	28.0	336	0.6428	0.4622	0.6428	0.8018
No log	29.0	348	0.7434	0.4350	0.7434	0.8622
No log	30.0	360	0.7601	0.4204	0.7601	0.8718
No log	31.0	372	0.8001	0.4231	0.8001	0.8945
No log	32.0	384	0.7080	0.4440	0.7080	0.8414
No log	33.0	396	0.6862	0.4303	0.6862	0.8283
No log	34.0	408	0.7713	0.4296	0.7713	0.8782
No log	35.0	420	0.6993	0.4228	0.6993	0.8362
No log	36.0	432	0.7419	0.4248	0.7419	0.8613
No log	37.0	444	0.7426	0.4151	0.7426	0.8618
No log	38.0	456	0.6978	0.4697	0.6978	0.8353
No log	39.0	468	0.7807	0.4253	0.7807	0.8835
No log	40.0	480	0.6538	0.4584	0.6538	0.8086
No log	41.0	492	0.6857	0.4106	0.6857	0.8281
0.3778	42.0	504	0.8095	0.4052	0.8095	0.8997
0.3778	43.0	516	0.6692	0.4498	0.6692	0.8180
0.3778	44.0	528	0.8590	0.3929	0.8590	0.9268
0.3778	45.0	540	0.6888	0.4357	0.6888	0.8299

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold0

ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold0