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	8.5591	0.0	8.5591	2.9256
No log	2.0	4	7.5775	0.0	7.5774	2.7527
No log	3.0	6	5.5762	0.0260	5.5764	2.3614
No log	4.0	8	4.4178	0.0039	4.4181	2.1019
No log	5.0	10	3.6751	0.0	3.6755	1.9171
No log	6.0	12	2.9033	0.0	2.9037	1.7040
No log	7.0	14	2.3121	0.1548	2.3126	1.5207
No log	8.0	16	1.8948	0.0640	1.8953	1.3767
No log	9.0	18	1.5489	0.0384	1.5493	1.2447
No log	10.0	20	1.2726	0.0213	1.2730	1.1283
No log	11.0	22	1.1045	0.0107	1.1049	1.0511
No log	12.0	24	0.9614	0.0213	0.9618	0.9807
No log	13.0	26	0.9346	0.0443	0.9349	0.9669
No log	14.0	28	0.9763	0.1091	0.9767	0.9883
No log	15.0	30	0.7309	0.4334	0.7312	0.8551
No log	16.0	32	0.6932	0.4365	0.6935	0.8328
No log	17.0	34	0.6489	0.4679	0.6492	0.8057
No log	18.0	36	0.7473	0.4911	0.7476	0.8646
No log	19.0	38	0.9389	0.4023	0.9392	0.9691
No log	20.0	40	0.9313	0.4036	0.9317	0.9652
No log	21.0	42	0.8060	0.4476	0.8064	0.8980
No log	22.0	44	0.5663	0.5197	0.5665	0.7526
No log	23.0	46	0.5141	0.5436	0.5143	0.7171
No log	24.0	48	0.6296	0.4863	0.6299	0.7936
No log	25.0	50	0.6013	0.4996	0.6015	0.7756
No log	26.0	52	0.6017	0.5378	0.6019	0.7758
No log	27.0	54	0.9798	0.4402	0.9799	0.9899
No log	28.0	56	0.9266	0.4779	0.9267	0.9627
No log	29.0	58	0.6760	0.5440	0.6761	0.8223
No log	30.0	60	0.6771	0.5593	0.6770	0.8228
No log	31.0	62	0.8064	0.4987	0.8064	0.8980
No log	32.0	64	0.7603	0.4696	0.7604	0.8720
No log	33.0	66	0.5575	0.5354	0.5574	0.7466
No log	34.0	68	0.7517	0.5225	0.7513	0.8668
No log	35.0	70	0.7203	0.5367	0.7198	0.8484
No log	36.0	72	0.5512	0.5962	0.5509	0.7422
No log	37.0	74	0.7702	0.4954	0.7701	0.8776
No log	38.0	76	0.7529	0.5039	0.7528	0.8677
No log	39.0	78	0.5384	0.5993	0.5383	0.7337
No log	40.0	80	0.6251	0.5981	0.6246	0.7903
No log	41.0	82	0.5793	0.6278	0.5787	0.7607
No log	42.0	84	0.6309	0.5856	0.6306	0.7941
No log	43.0	86	0.9031	0.4813	0.9029	0.9502
No log	44.0	88	0.8050	0.5221	0.8048	0.8971
No log	45.0	90	0.5725	0.6004	0.5721	0.7564
No log	46.0	92	0.6710	0.5853	0.6704	0.8188
No log	47.0	94	0.6007	0.6120	0.6002	0.7747
No log	48.0	96	0.6305	0.5814	0.6304	0.7940
No log	49.0	98	0.7522	0.4835	0.7522	0.8673
No log	50.0	100	0.6054	0.5730	0.6054	0.7781
No log	51.0	102	0.5436	0.5998	0.5434	0.7372
No log	52.0	104	0.5596	0.5942	0.5594	0.7479
No log	53.0	106	0.6199	0.5598	0.6198	0.7873
No log	54.0	108	0.5981	0.5961	0.5981	0.7733
No log	55.0	110	0.6234	0.6128	0.6232	0.7894
No log	56.0	112	0.6104	0.6067	0.6102	0.7812

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_lw040_fold2

Trial3BERT_AugV8_k1_task1_organization_sp010_lw040_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_sp010_lw040_fold2