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	10.9064	-0.0026	10.9067	3.3025
No log	2.0	6	8.0650	0.0	8.0651	2.8399
No log	3.0	9	5.4861	0.0195	5.4864	2.3423
No log	4.0	12	4.0063	0.0039	4.0067	2.0017
No log	5.0	15	2.9142	0.0	2.9146	1.7072
No log	6.0	18	2.1297	0.0929	2.1301	1.4595
No log	7.0	21	1.6060	0.0280	1.6065	1.2675
No log	8.0	24	1.2186	0.0107	1.2191	1.1041
No log	9.0	27	0.9817	0.0	0.9822	0.9911
No log	10.0	30	0.8251	0.3528	0.8255	0.9086
No log	11.0	33	0.7554	0.1195	0.7557	0.8693
No log	12.0	36	0.8797	0.0533	0.8801	0.9382
No log	13.0	39	0.8756	0.0636	0.8759	0.9359
No log	14.0	42	1.3519	0.1600	1.3521	1.1628
No log	15.0	45	1.5857	0.1640	1.5856	1.2592
No log	16.0	48	1.5323	0.2297	1.5319	1.2377
No log	17.0	51	0.7345	0.5042	0.7336	0.8565
No log	18.0	54	0.8856	0.5755	0.8838	0.9401
No log	19.0	57	1.2475	0.4550	1.2465	1.1165
No log	20.0	60	0.9370	0.5517	0.9359	0.9674
No log	21.0	63	0.6191	0.5694	0.6189	0.7867
No log	22.0	66	0.9328	0.5205	0.9321	0.9654
No log	23.0	69	0.7195	0.5443	0.7191	0.8480
No log	24.0	72	0.6011	0.5991	0.6007	0.7750
No log	25.0	75	0.9090	0.5464	0.9079	0.9528
No log	26.0	78	0.7624	0.5795	0.7623	0.8731
No log	27.0	81	0.6847	0.6091	0.6840	0.8270
No log	28.0	84	0.6854	0.6039	0.6849	0.8276
No log	29.0	87	0.7915	0.5689	0.7910	0.8894
No log	30.0	90	1.2470	0.4584	1.2458	1.1162
No log	31.0	93	0.7543	0.5856	0.7537	0.8681
No log	32.0	96	0.6889	0.5819	0.6890	0.8300
No log	33.0	99	0.7587	0.6034	0.7579	0.8706
No log	34.0	102	1.3643	0.4631	1.3625	1.1673
No log	35.0	105	0.8419	0.5607	0.8409	0.9170
No log	36.0	108	0.6443	0.6020	0.6438	0.8024
No log	37.0	111	0.7213	0.6008	0.7203	0.8487
No log	38.0	114	1.1196	0.4915	1.1180	1.0573
No log	39.0	117	0.8400	0.5810	0.8388	0.9159
No log	40.0	120	0.8334	0.5153	0.8332	0.9128
No log	41.0	123	0.8164	0.5085	0.8163	0.9035
No log	42.0	126	0.6267	0.5917	0.6260	0.7912
No log	43.0	129	1.1717	0.4566	1.1702	1.0818
No log	44.0	132	0.9296	0.5208	0.9283	0.9635
No log	45.0	135	0.7279	0.5748	0.7272	0.8527
No log	46.0	138	0.7541	0.5744	0.7534	0.8680
No log	47.0	141	0.7620	0.5810	0.7611	0.8724

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold2

Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version19ASAP_FineTuningBERT_AugV19_k10_task1_organization_k10_k10_fold2