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	8.2930	0.0	8.2904	2.8793
No log	2.0	4	7.3247	0.0	7.3222	2.7060
No log	3.0	6	5.9069	-0.0043	5.9046	2.4299
No log	4.0	8	4.6969	0.0143	4.6947	2.1667
No log	5.0	10	3.8916	0.0	3.8897	1.9722
No log	6.0	12	3.0523	0.0	3.0505	1.7466
No log	7.0	14	2.7996	0.0	2.7978	1.6727
No log	8.0	16	2.3277	0.0441	2.3260	1.5251
No log	9.0	18	1.6616	0.1015	1.6599	1.2884
No log	10.0	20	1.3334	0.0872	1.3319	1.1541
No log	11.0	22	1.2337	0.0106	1.2323	1.1101
No log	12.0	24	0.9517	0.0482	0.9504	0.9749
No log	13.0	26	1.3828	0.1258	1.3812	1.1753
No log	14.0	28	1.0327	0.1125	1.0312	1.0155
No log	15.0	30	0.8872	0.1780	0.8861	0.9413
No log	16.0	32	0.9243	0.1411	0.9233	0.9609
No log	17.0	34	0.6819	0.3354	0.6810	0.8252
No log	18.0	36	1.0064	0.2337	1.0051	1.0026
No log	19.0	38	1.1069	0.2086	1.1056	1.0515
No log	20.0	40	0.6424	0.4704	0.6413	0.8008
No log	21.0	42	0.8913	0.2604	0.8906	0.9437
No log	22.0	44	1.0177	0.2167	1.0170	1.0085
No log	23.0	46	0.8714	0.3512	0.8708	0.9332
No log	24.0	48	0.5244	0.5777	0.5238	0.7237
No log	25.0	50	0.8138	0.5831	0.8131	0.9017
No log	26.0	52	0.6740	0.5992	0.6732	0.8205
No log	27.0	54	0.6543	0.5336	0.6533	0.8083
No log	28.0	56	0.7273	0.4304	0.7265	0.8523
No log	29.0	58	0.6307	0.4558	0.6297	0.7936
No log	30.0	60	0.5346	0.5491	0.5335	0.7304
No log	31.0	62	0.5831	0.5446	0.5819	0.7628
No log	32.0	64	0.5591	0.5169	0.5580	0.7470
No log	33.0	66	0.6505	0.4565	0.6496	0.8060
No log	34.0	68	0.6138	0.4908	0.6129	0.7829
No log	35.0	70	0.5255	0.5899	0.5244	0.7242
No log	36.0	72	0.5745	0.5831	0.5732	0.7571
No log	37.0	74	0.5499	0.5674	0.5489	0.7409
No log	38.0	76	0.7375	0.4438	0.7367	0.8583
No log	39.0	78	0.9107	0.3290	0.9100	0.9540
No log	40.0	80	0.9443	0.3620	0.9436	0.9714
No log	41.0	82	0.8148	0.4500	0.8143	0.9024
No log	42.0	84	0.5576	0.5369	0.5570	0.7464
No log	43.0	86	0.5488	0.5636	0.5483	0.7404
No log	44.0	88	0.7295	0.4874	0.7291	0.8539
No log	45.0	90	0.8661	0.3655	0.8657	0.9304
No log	46.0	92	0.7675	0.4061	0.7670	0.8758

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV16_k1_task1_organization_k1_k1_fold1

ASAP_FineTuningBERT_AugV16_k1_task1_organization_k1_k1_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV16_k1_task1_organization_k1_k1_fold1