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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	1	13.2646	0.0	13.2646	3.6421
No log	2.0	2	11.4653	0.0062	11.4653	3.3860
No log	3.0	3	9.6471	0.0060	9.6471	3.1060
No log	4.0	4	9.1072	0.0016	9.1072	3.0178
No log	5.0	5	8.1343	0.0018	8.1343	2.8521
No log	6.0	6	6.8797	0.0018	6.8797	2.6229
No log	7.0	7	6.1057	0.0161	6.1057	2.4710
No log	8.0	8	5.3575	0.0565	5.3575	2.3146
No log	9.0	9	4.5719	0.0200	4.5719	2.1382
No log	10.0	10	3.8390	0.0142	3.8390	1.9593
No log	11.0	11	3.5543	0.0040	3.5543	1.8853
No log	12.0	12	3.0195	0.0040	3.0195	1.7377
No log	13.0	13	2.6053	0.0223	2.6053	1.6141
No log	14.0	14	2.1415	0.1277	2.1415	1.4634
No log	15.0	15	1.8622	0.1179	1.8622	1.3646
No log	16.0	16	1.6665	0.0668	1.6665	1.2909
No log	17.0	17	1.4201	0.0668	1.4201	1.1917
No log	18.0	18	1.2705	0.0509	1.2705	1.1271
No log	19.0	19	1.1581	0.0484	1.1581	1.0762
No log	20.0	20	1.0452	0.0484	1.0452	1.0224
No log	21.0	21	0.9208	0.0903	0.9208	0.9596
No log	22.0	22	0.8316	0.2759	0.8316	0.9119
No log	23.0	23	0.9025	0.1730	0.9025	0.9500
No log	24.0	24	0.8556	0.2783	0.8556	0.9250
No log	25.0	25	0.6767	0.4431	0.6767	0.8226
No log	26.0	26	0.6405	0.4449	0.6405	0.8003
No log	27.0	27	0.5987	0.4752	0.5987	0.7738
No log	28.0	28	0.7461	0.4231	0.7461	0.8638
No log	29.0	29	0.7706	0.4113	0.7706	0.8779
No log	30.0	30	0.6165	0.5036	0.6165	0.7851
No log	31.0	31	0.5557	0.5320	0.5557	0.7455
No log	32.0	32	0.5516	0.5590	0.5516	0.7427
No log	33.0	33	0.6485	0.5088	0.6485	0.8053
No log	34.0	34	0.6994	0.4999	0.6994	0.8363
No log	35.0	35	0.5938	0.5584	0.5938	0.7706
No log	36.0	36	0.5405	0.5422	0.5405	0.7352
No log	37.0	37	0.5511	0.5275	0.5511	0.7423
No log	38.0	38	0.5553	0.5665	0.5553	0.7452
No log	39.0	39	0.5818	0.5697	0.5818	0.7627
No log	40.0	40	0.5909	0.5802	0.5909	0.7687
No log	41.0	41	0.6823	0.5770	0.6823	0.8260
No log	42.0	42	0.6525	0.5960	0.6525	0.8078
No log	43.0	43	0.6115	0.5810	0.6115	0.7820
No log	44.0	44	0.6469	0.6123	0.6469	0.8043
No log	45.0	45	0.6756	0.5800	0.6756	0.8219
No log	46.0	46	0.6388	0.5796	0.6388	0.7993
No log	47.0	47	0.6382	0.5723	0.6382	0.7989
No log	48.0	48	0.6391	0.5645	0.6391	0.7995
No log	49.0	49	0.6391	0.5603	0.6391	0.7994
No log	50.0	50	0.6622	0.5773	0.6622	0.8138
No log	51.0	51	0.8090	0.5428	0.8090	0.8994
No log	52.0	52	0.8381	0.5439	0.8381	0.9155
No log	53.0	53	0.7334	0.5892	0.7334	0.8564
No log	54.0	54	0.6901	0.5684	0.6901	0.8307
No log	55.0	55	0.7595	0.5307	0.7595	0.8715
No log	56.0	56	0.7147	0.5490	0.7147	0.8454
No log	57.0	57	0.6708	0.5583	0.6708	0.8190
No log	58.0	58	0.8157	0.5678	0.8157	0.9032
No log	59.0	59	0.8718	0.5433	0.8718	0.9337

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Trial3BERT_AugV8_k1_task1_organization_sp010_lw010_fold4

Trial3BERT_AugV8_k1_task1_organization_sp010_lw010_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_sp010_lw010_fold4