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	8.2450	0.0	8.2450	2.8714
No log	2.0	6	6.9375	0.0	6.9375	2.6339
No log	3.0	9	5.8932	0.0050	5.8932	2.4276
No log	4.0	12	4.6647	0.0077	4.6647	2.1598
No log	5.0	15	3.6873	0.0039	3.6873	1.9202
No log	6.0	18	2.6387	0.0	2.6387	1.6244
No log	7.0	21	1.8221	0.0316	1.8221	1.3499
No log	8.0	24	1.3105	0.0316	1.3105	1.1448
No log	9.0	27	0.9885	0.0106	0.9885	0.9942
No log	10.0	30	0.7885	0.2091	0.7885	0.8880
No log	11.0	33	0.7958	0.0689	0.7958	0.8921
No log	12.0	36	0.8401	0.0689	0.8401	0.9166
No log	13.0	39	1.1159	0.0521	1.1159	1.0564
No log	14.0	42	1.2454	0.2010	1.2454	1.1160
No log	15.0	45	1.3474	0.1741	1.3474	1.1608
No log	16.0	48	1.0803	0.3386	1.0803	1.0394
No log	17.0	51	0.5568	0.5398	0.5568	0.7462
No log	18.0	54	1.1882	0.3872	1.1882	1.0901
No log	19.0	57	0.4997	0.5903	0.4997	0.7069
No log	20.0	60	0.9149	0.3811	0.9149	0.9565
No log	21.0	63	0.6019	0.5601	0.6019	0.7758
No log	22.0	66	0.7918	0.5811	0.7918	0.8898
No log	23.0	69	0.5576	0.6366	0.5576	0.7467
No log	24.0	72	0.5772	0.6105	0.5772	0.7597
No log	25.0	75	0.5581	0.6688	0.5581	0.7471
No log	26.0	78	0.4830	0.6398	0.4830	0.6950
No log	27.0	81	0.8027	0.5734	0.8027	0.8959
No log	28.0	84	0.8653	0.5295	0.8653	0.9302
No log	29.0	87	0.4948	0.5842	0.4948	0.7034
No log	30.0	90	0.6010	0.5633	0.6010	0.7752
No log	31.0	93	0.6859	0.6144	0.6859	0.8282
No log	32.0	96	1.0401	0.5481	1.0401	1.0199
No log	33.0	99	0.4861	0.6614	0.4861	0.6972
No log	34.0	102	0.5109	0.6264	0.5109	0.7148
No log	35.0	105	0.6290	0.6355	0.6290	0.7931
No log	36.0	108	0.6226	0.6378	0.6226	0.7890
No log	37.0	111	0.5035	0.6000	0.5035	0.7096
No log	38.0	114	0.4862	0.6108	0.4862	0.6973
No log	39.0	117	0.8899	0.5578	0.8899	0.9433
No log	40.0	120	0.9891	0.5088	0.9891	0.9946
No log	41.0	123	0.5092	0.6477	0.5092	0.7136
No log	42.0	126	0.5384	0.6387	0.5384	0.7338
No log	43.0	129	0.5303	0.6489	0.5303	0.7282
No log	44.0	132	0.5765	0.6424	0.5765	0.7593
No log	45.0	135	0.5587	0.6307	0.5587	0.7475

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold0

Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12AGAINNNASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold0