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	3	8.3805	0.0	8.3779	2.8945
No log	2.0	6	5.7072	-0.0236	5.7050	2.3885
No log	3.0	9	4.1011	0.0118	4.0991	2.0246
No log	4.0	12	3.2627	0.0	3.2607	1.8057
No log	5.0	15	2.2592	0.1455	2.2575	1.5025
No log	6.0	18	1.6701	0.0315	1.6684	1.2917
No log	7.0	21	1.3247	0.0106	1.3232	1.1503
No log	8.0	24	0.9513	0.0	0.9501	0.9747
No log	9.0	27	0.9583	0.0107	0.9571	0.9783
No log	10.0	30	0.8319	0.1347	0.8308	0.9115
No log	11.0	33	0.8984	0.0571	0.8974	0.9473
No log	12.0	36	1.0281	0.0571	1.0273	1.0136
No log	13.0	39	0.9017	0.2022	0.9011	0.9493
No log	14.0	42	0.8839	0.4103	0.8834	0.9399
No log	15.0	45	1.0030	0.4284	1.0027	1.0014
No log	16.0	48	0.4941	0.5997	0.4936	0.7025
No log	17.0	51	0.6896	0.5839	0.6893	0.8303
No log	18.0	54	0.6227	0.6283	0.6225	0.7890
No log	19.0	57	0.4895	0.6711	0.4891	0.6994
No log	20.0	60	1.0862	0.5599	1.0865	1.0423
No log	21.0	63	0.5023	0.6778	0.5019	0.7084
No log	22.0	66	0.4306	0.7124	0.4302	0.6559
No log	23.0	69	1.1775	0.5355	1.1777	1.0852
No log	24.0	72	0.5027	0.6741	0.5024	0.7088
No log	25.0	75	0.9590	0.5758	0.9591	0.9793
No log	26.0	78	0.4874	0.6840	0.4873	0.6980
No log	27.0	81	1.1750	0.5490	1.1754	1.0842
No log	28.0	84	0.4784	0.7160	0.4782	0.6916
No log	29.0	87	0.7879	0.6226	0.7881	0.8877
No log	30.0	90	1.6290	0.4560	1.6295	1.2765
No log	31.0	93	0.7876	0.6206	0.7878	0.8876
No log	32.0	96	1.1001	0.5606	1.1005	1.0490
No log	33.0	99	0.6988	0.6322	0.6990	0.8360
No log	34.0	102	1.1068	0.5665	1.1072	1.0522
No log	35.0	105	0.6385	0.6311	0.6385	0.7991
No log	36.0	108	0.8561	0.5779	0.8562	0.9253
No log	37.0	111	1.5167	0.4578	1.5169	1.2316
No log	38.0	114	0.6080	0.6609	0.6081	0.7798
No log	39.0	117	0.9653	0.5645	0.9653	0.9825
No log	40.0	120	0.8774	0.5579	0.8773	0.9366
No log	41.0	123	0.7915	0.5855	0.7914	0.8896
No log	42.0	126	0.8336	0.6001	0.8336	0.9130
No log	43.0	129	0.6224	0.6446	0.6223	0.7889
No log	44.0	132	1.4476	0.4446	1.4476	1.2032
No log	45.0	135	1.7144	0.3900	1.7143	1.3093
No log	46.0	138	0.9412	0.5247	0.9409	0.9700
No log	47.0	141	0.6310	0.6314	0.6308	0.7942
No log	48.0	144	0.8723	0.5893	0.8723	0.9340

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold1

Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold1