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	10.8499	0.0125	10.8469	3.2935
No log	2.0	2	9.9370	0.0	9.9344	3.1519
No log	3.0	3	9.6107	0.0	9.6081	3.0997
No log	4.0	4	9.3707	0.0	9.3681	3.0607
No log	5.0	5	9.0720	0.0	9.0695	3.0116
No log	6.0	6	8.5402	0.0	8.5376	2.9219
No log	7.0	7	7.5301	0.0	7.5277	2.7437
No log	8.0	8	6.7152	0.0	6.7129	2.5909
No log	9.0	9	6.5974	0.0	6.5951	2.5681
No log	10.0	10	6.0940	-0.0023	6.0918	2.4681
No log	11.0	11	5.3488	0.0020	5.3466	2.3123
No log	12.0	12	4.6680	0.0	4.6659	2.1601
No log	13.0	13	4.2272	0.0	4.2252	2.0555
No log	14.0	14	3.8319	0.0	3.8299	1.9570
No log	15.0	15	3.4355	0.0	3.4336	1.8530
No log	16.0	16	3.1172	0.0	3.1153	1.7650
No log	17.0	17	2.8750	0.0	2.8731	1.6950
No log	18.0	18	2.6530	0.0	2.6512	1.6282
No log	19.0	19	2.3851	-0.0157	2.3833	1.5438
No log	20.0	20	2.1233	0.0530	2.1216	1.4566
No log	21.0	21	1.9170	0.0315	1.9153	1.3839
No log	22.0	22	1.7535	0.0211	1.7519	1.3236
No log	23.0	23	1.6102	0.0	1.6086	1.2683
No log	24.0	24	1.4800	0.0	1.4785	1.2159
No log	25.0	25	1.3746	0.0	1.3731	1.1718
No log	26.0	26	1.2717	0.0	1.2703	1.1271
No log	27.0	27	1.1633	0.0	1.1619	1.0779
No log	28.0	28	1.0824	0.0	1.0810	1.0397
No log	29.0	29	1.0437	0.0	1.0423	1.0209
No log	30.0	30	0.9834	0.0	0.9821	0.9910
No log	31.0	31	0.9053	0.0	0.9041	0.9508
No log	32.0	32	0.8268	0.4597	0.8256	0.9086
No log	33.0	33	0.7864	0.4435	0.7852	0.8861
No log	34.0	34	0.7454	0.4130	0.7442	0.8627
No log	35.0	35	0.7162	0.4018	0.7150	0.8456
No log	36.0	36	0.6412	0.4844	0.6401	0.8001
No log	37.0	37	0.6417	0.4702	0.6406	0.8004
No log	38.0	38	0.6046	0.4877	0.6036	0.7769
No log	39.0	39	0.5803	0.5113	0.5792	0.7611
No log	40.0	40	0.5473	0.5376	0.5463	0.7391
No log	41.0	41	0.5651	0.5210	0.5641	0.7510
No log	42.0	42	0.5730	0.5294	0.5720	0.7563
No log	43.0	43	0.5600	0.5560	0.5590	0.7477
No log	44.0	44	0.5175	0.5847	0.5167	0.7188
No log	45.0	45	0.5886	0.5575	0.5877	0.7666
No log	46.0	46	0.6518	0.4874	0.6509	0.8068
No log	47.0	47	0.5642	0.5927	0.5634	0.7506
No log	48.0	48	0.6854	0.5424	0.6846	0.8274
No log	49.0	49	0.9510	0.3554	0.9502	0.9748
No log	50.0	50	0.9383	0.3999	0.9375	0.9682
No log	51.0	51	0.6654	0.6247	0.6647	0.8153
No log	52.0	52	0.5552	0.6682	0.5546	0.7447
No log	53.0	53	0.6466	0.6400	0.6460	0.8037
No log	54.0	54	0.9526	0.4970	0.9519	0.9757
No log	55.0	55	1.0559	0.4519	1.0552	1.0272
No log	56.0	56	0.8991	0.5186	0.8985	0.9479
No log	57.0	57	0.6072	0.6629	0.6067	0.7789
No log	58.0	58	0.5739	0.6694	0.5734	0.7573
No log	59.0	59	0.7005	0.6361	0.7000	0.8367
No log	60.0	60	1.0079	0.5068	1.0073	1.0037
No log	61.0	61	1.1831	0.4587	1.1826	1.0875
No log	62.0	62	1.0820	0.5032	1.0815	1.0399
No log	63.0	63	0.7734	0.6156	0.7730	0.8792
No log	64.0	64	0.5338	0.6804	0.5334	0.7304
No log	65.0	65	0.5222	0.6844	0.5218	0.7224
No log	66.0	66	0.5333	0.6860	0.5329	0.7300
No log	67.0	67	0.6659	0.6442	0.6656	0.8158
No log	68.0	68	1.0376	0.5464	1.0371	1.0184
No log	69.0	69	1.2251	0.4898	1.2246	1.1066
No log	70.0	70	1.1662	0.5048	1.1657	1.0797
No log	71.0	71	0.9221	0.5688	0.9217	0.9600
No log	72.0	72	0.6468	0.6514	0.6465	0.8040
No log	73.0	73	0.5738	0.6502	0.5734	0.7572
No log	74.0	74	0.6032	0.6515	0.6028	0.7764
No log	75.0	75	0.7417	0.6430	0.7413	0.8610
No log	76.0	76	1.0325	0.5531	1.0321	1.0159
No log	77.0	77	1.1817	0.5194	1.1813	1.0869
No log	78.0	78	1.1507	0.5322	1.1503	1.0725
No log	79.0	79	0.9946	0.5740	0.9942	0.9971
No log	80.0	80	0.7772	0.6380	0.7769	0.8814
No log	81.0	81	0.7090	0.6463	0.7087	0.8418
No log	82.0	82	0.7361	0.6497	0.7357	0.8578
No log	83.0	83	0.8513	0.6201	0.8509	0.9225
No log	84.0	84	1.0666	0.5631	1.0662	1.0326
No log	85.0	85	1.2299	0.5288	1.2295	1.1088
No log	86.0	86	1.3146	0.5126	1.3142	1.1464

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold1

Version3ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold1