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	4	6.9752	0.0	6.9740	2.6408
No log	2.0	8	5.3078	0.0076	5.3066	2.3036
No log	3.0	12	3.6947	0.0	3.6936	1.9219
No log	4.0	16	2.4283	0.1028	2.4275	1.5580
No log	5.0	20	1.6305	0.0202	1.6297	1.2766
No log	6.0	24	2.1994	0.0051	2.1981	1.4826
No log	7.0	28	1.0447	0.0302	1.0443	1.0219
No log	8.0	32	1.5045	0.1061	1.5039	1.2263
No log	9.0	36	1.2620	0.0567	1.2615	1.1232
No log	10.0	40	2.0385	0.1604	2.0378	1.4275
No log	11.0	44	2.0340	0.1682	2.0334	1.4260
No log	12.0	48	1.5798	0.2335	1.5793	1.2567
No log	13.0	52	0.8457	0.3062	0.8455	0.9195
No log	14.0	56	1.7879	0.1671	1.7873	1.3369
No log	15.0	60	0.7635	0.3307	0.7636	0.8738
No log	16.0	64	1.3850	0.2767	1.3848	1.1768
No log	17.0	68	1.1050	0.3174	1.1050	1.0512
No log	18.0	72	0.8469	0.3811	0.8473	0.9205
No log	19.0	76	0.8370	0.3827	0.8376	0.9152
No log	20.0	80	0.7862	0.4105	0.7866	0.8869
No log	21.0	84	0.6826	0.3867	0.6829	0.8264
No log	22.0	88	0.9688	0.3716	0.9692	0.9845
No log	23.0	92	0.7458	0.4413	0.7463	0.8639
No log	24.0	96	0.7376	0.4655	0.7380	0.8591
No log	25.0	100	1.3780	0.2443	1.3780	1.1739
No log	26.0	104	0.7556	0.4343	0.7559	0.8694
No log	27.0	108	1.1636	0.3397	1.1639	1.0788
No log	28.0	112	0.7396	0.4284	0.7399	0.8602
No log	29.0	116	1.4714	0.2583	1.4715	1.2131
No log	30.0	120	0.7231	0.4318	0.7235	0.8506
No log	31.0	124	1.1816	0.3016	1.1820	1.0872
No log	32.0	128	0.8289	0.4362	0.8294	0.9107
No log	33.0	132	1.1553	0.3223	1.1558	1.0751
No log	34.0	136	0.7562	0.4510	0.7566	0.8698
No log	35.0	140	0.9120	0.3888	0.9124	0.9552
No log	36.0	144	0.7584	0.4504	0.7587	0.8711
No log	37.0	148	0.7593	0.4262	0.7596	0.8716
No log	38.0	152	0.7516	0.4369	0.7520	0.8672
No log	39.0	156	0.8986	0.4592	0.8989	0.9481
No log	40.0	160	0.7576	0.4501	0.7579	0.8706
No log	41.0	164	0.8815	0.4340	0.8817	0.9390
No log	42.0	168	0.8699	0.4460	0.8702	0.9328
No log	43.0	172	0.8770	0.4505	0.8774	0.9367
No log	44.0	176	0.7649	0.4524	0.7652	0.8748

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold3

Version3ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3ASAP_FineTuningBERT_AugV14_k5_task1_organization_k5_k5_fold3