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	2	12.7782	0.0	12.7782	3.5747
No log	2.0	4	11.1925	0.0061	11.1925	3.3455
No log	3.0	6	9.6819	0.0	9.6819	3.1116
No log	4.0	8	8.1063	0.0	8.1063	2.8472
No log	5.0	10	6.4239	0.0011	6.4239	2.5346
No log	6.0	12	4.7418	0.0115	4.7418	2.1776
No log	7.0	14	3.5383	0.0077	3.5383	1.8810
No log	8.0	16	2.5364	0.0431	2.5364	1.5926
No log	9.0	18	1.9236	0.0419	1.9236	1.3869
No log	10.0	20	1.6049	0.0316	1.6049	1.2668
No log	11.0	22	1.2814	0.0316	1.2814	1.1320
No log	12.0	24	1.0977	0.0316	1.0977	1.0477
No log	13.0	26	0.9835	0.0316	0.9835	0.9917
No log	14.0	28	1.1267	0.0344	1.1267	1.0615
No log	15.0	30	0.9742	0.1848	0.9742	0.9870
No log	16.0	32	0.7455	0.3898	0.7455	0.8634
No log	17.0	34	0.7894	0.3769	0.7894	0.8885
No log	18.0	36	0.7628	0.3874	0.7628	0.8734
No log	19.0	38	0.6189	0.3796	0.6189	0.7867
No log	20.0	40	0.6119	0.3862	0.6119	0.7822
No log	21.0	42	0.7181	0.3928	0.7181	0.8474
No log	22.0	44	0.6048	0.4159	0.6048	0.7777
No log	23.0	46	0.6438	0.3234	0.6438	0.8024
No log	24.0	48	0.6024	0.3924	0.6024	0.7761
No log	25.0	50	0.7078	0.4320	0.7078	0.8413
No log	26.0	52	0.6553	0.4397	0.6553	0.8095
No log	27.0	54	0.7707	0.4754	0.7707	0.8779
No log	28.0	56	0.7653	0.4520	0.7653	0.8748
No log	29.0	58	0.7439	0.4635	0.7439	0.8625
No log	30.0	60	0.8201	0.4328	0.8201	0.9056
No log	31.0	62	1.1329	0.2936	1.1329	1.0644
No log	32.0	64	1.0359	0.3480	1.0359	1.0178
No log	33.0	66	0.7633	0.4534	0.7633	0.8737
No log	34.0	68	0.7843	0.4395	0.7843	0.8856
No log	35.0	70	1.1270	0.3275	1.1270	1.0616
No log	36.0	72	1.3226	0.2889	1.3226	1.1500
No log	37.0	74	1.1316	0.3400	1.1316	1.0637
No log	38.0	76	0.8866	0.4110	0.8866	0.9416
No log	39.0	78	0.8792	0.4110	0.8792	0.9377
No log	40.0	80	1.1830	0.2965	1.1830	1.0877
No log	41.0	82	1.2320	0.2966	1.2320	1.1100
No log	42.0	84	0.8503	0.4173	0.8503	0.9221
No log	43.0	86	0.7712	0.4341	0.7712	0.8782
No log	44.0	88	0.8089	0.4173	0.8089	0.8994
No log	45.0	90	0.8549	0.4211	0.8549	0.9246
No log	46.0	92	0.8642	0.4203	0.8642	0.9296
No log	47.0	94	0.8785	0.4480	0.8785	0.9373

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold0

Version3ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold0