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	2	9.8619	-0.0035	9.8588	3.1399
No log	2.0	4	8.6096	0.0	8.6068	2.9337
No log	3.0	6	7.6264	0.0	7.6237	2.7611
No log	4.0	8	6.4867	0.0	6.4843	2.5464
No log	5.0	10	5.1248	0.0323	5.1227	2.2633
No log	6.0	12	3.9552	-0.0073	3.9532	1.9883
No log	7.0	14	3.3429	0.0	3.3412	1.8279
No log	8.0	16	2.5384	0.0268	2.5368	1.5927
No log	9.0	18	1.8978	0.1413	1.8962	1.3770
No log	10.0	20	1.6124	0.0486	1.6108	1.2692
No log	11.0	22	1.2139	-0.0143	1.2125	1.1011
No log	12.0	24	1.1486	0.0	1.1473	1.0711
No log	13.0	26	0.9761	0.0273	0.9748	0.9873
No log	14.0	28	0.8270	0.3556	0.8257	0.9087
No log	15.0	30	0.7774	0.4184	0.7762	0.8810
No log	16.0	32	0.7923	0.3198	0.7913	0.8895
No log	17.0	34	1.0805	-0.1378	1.0794	1.0389
No log	18.0	36	1.1081	-0.0242	1.1071	1.0522
No log	19.0	38	0.8012	0.3767	0.8004	0.8947
No log	20.0	40	0.7044	0.4639	0.7037	0.8388
No log	21.0	42	0.6704	0.4877	0.6697	0.8183
No log	22.0	44	0.7808	0.3976	0.7801	0.8832
No log	23.0	46	0.9376	0.2595	0.9369	0.9679
No log	24.0	48	0.8444	0.2755	0.8438	0.9186
No log	25.0	50	0.7875	0.3814	0.7869	0.8871
No log	26.0	52	1.1088	0.3156	1.1079	1.0526
No log	27.0	54	1.2604	0.3064	1.2595	1.1223
No log	28.0	56	0.8316	0.4234	0.8308	0.9115
No log	29.0	58	0.7814	0.4799	0.7809	0.8837
No log	30.0	60	0.7754	0.4774	0.7749	0.8803
No log	31.0	62	0.6287	0.5332	0.6282	0.7926
No log	32.0	64	0.6563	0.4932	0.6556	0.8097
No log	33.0	66	0.8260	0.4508	0.8252	0.9084
No log	34.0	68	0.8911	0.3523	0.8905	0.9436
No log	35.0	70	1.0536	0.2545	1.0530	1.0262
No log	36.0	72	1.2534	0.2509	1.2532	1.1195
No log	37.0	74	1.0562	0.3550	1.0560	1.0276
No log	38.0	76	0.6634	0.5374	0.6629	0.8142
No log	39.0	78	0.8468	0.4686	0.8458	0.9197
No log	40.0	80	1.1437	0.3512	1.1424	1.0688
No log	41.0	82	0.9100	0.3888	0.9089	0.9534
No log	42.0	84	0.7626	0.4096	0.7619	0.8729
No log	43.0	86	1.1038	0.2695	1.1034	1.0505
No log	44.0	88	1.2617	0.1746	1.2613	1.1231
No log	45.0	90	1.1928	0.1963	1.1921	1.0918
No log	46.0	92	1.1342	0.2652	1.1333	1.0646
No log	47.0	94	1.0245	0.3662	1.0238	1.0118
No log	48.0	96	0.8866	0.4623	0.8860	0.9413
No log	49.0	98	0.8546	0.4721	0.8540	0.9241
No log	50.0	100	0.8483	0.4404	0.8475	0.9206
No log	51.0	102	0.8420	0.3850	0.8411	0.9171
No log	52.0	104	0.8373	0.3843	0.8364	0.9146
No log	53.0	106	0.8344	0.3821	0.8336	0.9130

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/BERT_AugV8_k1_task1_organization_sp010_lw040_fold1

BERT_AugV8_k1_task1_organization_sp010_lw040_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
BERT_AugV8_k1_task1_organization_sp010_lw040_fold1