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	1	8.8910	0.0	8.8910	2.9818
No log	2.0	2	7.5729	0.0	7.5729	2.7519
No log	3.0	3	6.5954	0.0	6.5954	2.5682
No log	4.0	4	6.0439	0.0	6.0439	2.4584
No log	5.0	5	5.5804	0.0323	5.5804	2.3623
No log	6.0	6	4.8816	0.0121	4.8816	2.2094
No log	7.0	7	4.1214	0.0180	4.1214	2.0301
No log	8.0	8	3.5423	0.0	3.5423	1.8821
No log	9.0	9	3.1277	0.0	3.1277	1.7685
No log	10.0	10	2.9234	0.0	2.9234	1.7098
No log	11.0	11	2.6648	0.0	2.6648	1.6324
No log	12.0	12	2.3466	0.0087	2.3466	1.5319
No log	13.0	13	1.9959	0.1008	1.9959	1.4128
No log	14.0	14	1.7032	0.0747	1.7032	1.3051
No log	15.0	15	1.5295	0.0472	1.5295	1.2367
No log	16.0	16	1.3775	0.0472	1.3775	1.1737
No log	17.0	17	1.2990	0.0	1.2990	1.1397
No log	18.0	18	1.2178	0.0	1.2178	1.1035
No log	19.0	19	1.1195	0.0	1.1195	1.0581
No log	20.0	20	1.0218	0.0	1.0218	1.0108
No log	21.0	21	0.9566	0.0	0.9566	0.9781
No log	22.0	22	0.9313	0.3187	0.9313	0.9651
No log	23.0	23	0.9316	0.1595	0.9316	0.9652
No log	24.0	24	0.9147	0.1037	0.9147	0.9564
No log	25.0	25	0.9035	0.1037	0.9035	0.9505
No log	26.0	26	0.9047	0.1037	0.9047	0.9512
No log	27.0	27	0.9129	0.0909	0.9129	0.9554
No log	28.0	28	0.9181	0.0909	0.9181	0.9582
No log	29.0	29	0.9346	0.0909	0.9346	0.9667
No log	30.0	30	0.9630	0.0909	0.9630	0.9813
No log	31.0	31	0.9852	0.0909	0.9852	0.9926
No log	32.0	32	0.9714	0.1037	0.9714	0.9856
No log	33.0	33	0.8718	0.1037	0.8718	0.9337
No log	34.0	34	0.7631	0.3542	0.7631	0.8736
No log	35.0	35	0.7197	0.4399	0.7197	0.8483
No log	36.0	36	0.7314	0.5336	0.7314	0.8552
No log	37.0	37	0.6848	0.6635	0.6848	0.8275
No log	38.0	38	0.6091	0.6499	0.6091	0.7804
No log	39.0	39	0.5308	0.6703	0.5308	0.7286
No log	40.0	40	0.5084	0.6588	0.5084	0.7130
No log	41.0	41	0.5502	0.6375	0.5502	0.7418
No log	42.0	42	0.5229	0.6486	0.5229	0.7231
No log	43.0	43	0.5533	0.6819	0.5533	0.7439
No log	44.0	44	0.7003	0.6112	0.7003	0.8369
No log	45.0	45	0.7800	0.6203	0.7800	0.8832
No log	46.0	46	0.6653	0.6341	0.6653	0.8157
No log	47.0	47	0.5891	0.6939	0.5891	0.7675
No log	48.0	48	0.6623	0.6474	0.6623	0.8138
No log	49.0	49	0.7821	0.6202	0.7821	0.8843
No log	50.0	50	0.7302	0.6275	0.7302	0.8545
No log	51.0	51	0.6083	0.6980	0.6083	0.7800
No log	52.0	52	0.6210	0.6980	0.6210	0.7880
No log	53.0	53	0.7821	0.6218	0.7821	0.8844
No log	54.0	54	0.9481	0.6186	0.9481	0.9737
No log	55.0	55	0.9367	0.6186	0.9367	0.9678
No log	56.0	56	0.7605	0.6680	0.7605	0.8721
No log	57.0	57	0.7159	0.6881	0.7159	0.8461
No log	58.0	58	0.8401	0.6763	0.8401	0.9166
No log	59.0	59	0.8667	0.6505	0.8667	0.9310
No log	60.0	60	0.7314	0.6869	0.7314	0.8552
No log	61.0	61	0.7056	0.6965	0.7056	0.8400
No log	62.0	62	0.8055	0.6712	0.8055	0.8975
No log	63.0	63	1.0364	0.6401	1.0364	1.0180
No log	64.0	64	0.9862	0.6378	0.9862	0.9931
No log	65.0	65	0.7511	0.6752	0.7511	0.8667
No log	66.0	66	0.7413	0.6752	0.7413	0.8610
No log	67.0	67	0.9020	0.6376	0.9020	0.9497
No log	68.0	68	1.1473	0.5896	1.1473	1.0711
No log	69.0	69	1.1436	0.5896	1.1436	1.0694
No log	70.0	70	0.9474	0.6526	0.9474	0.9733
No log	71.0	71	0.6687	0.6912	0.6687	0.8178

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12LowDevASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold1

Version12LowDevASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12LowDevASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold1