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	8.0759	0.0018	8.0759	2.8418
No log	2.0	6	6.3817	0.0	6.3817	2.5262
No log	3.0	9	4.8181	0.0040	4.8181	2.1950
No log	4.0	12	3.0260	0.0040	3.0260	1.7395
No log	5.0	15	2.3984	0.1376	2.3984	1.5487
No log	6.0	18	1.8965	0.0881	1.8965	1.3771
No log	7.0	21	1.6728	0.0408	1.6728	1.2934
No log	8.0	24	1.4075	0.0344	1.4075	1.1864
No log	9.0	27	1.3631	0.0610	1.3631	1.1675
No log	10.0	30	1.5079	0.0814	1.5079	1.2280
No log	11.0	33	1.5958	0.1946	1.5958	1.2632
No log	12.0	36	1.2569	0.1279	1.2569	1.1211
No log	13.0	39	1.8056	0.2011	1.8056	1.3437
No log	14.0	42	1.5695	0.2200	1.5695	1.2528
No log	15.0	45	0.6986	0.4618	0.6986	0.8358
No log	16.0	48	1.4798	0.2720	1.4798	1.2165
No log	17.0	51	1.1179	0.3581	1.1179	1.0573
No log	18.0	54	0.6459	0.4572	0.6459	0.8037
No log	19.0	57	1.4874	0.2717	1.4874	1.2196
No log	20.0	60	0.9412	0.4012	0.9412	0.9702
No log	21.0	63	0.9408	0.4057	0.9408	0.9700
No log	22.0	66	1.0831	0.3723	1.0831	1.0407
No log	23.0	69	0.9873	0.4285	0.9873	0.9936
No log	24.0	72	0.8747	0.4751	0.8747	0.9353
No log	25.0	75	0.8954	0.4679	0.8954	0.9462
No log	26.0	78	0.8685	0.4570	0.8685	0.9320
No log	27.0	81	0.9849	0.4360	0.9849	0.9924
No log	28.0	84	0.7544	0.4651	0.7544	0.8685
No log	29.0	87	1.3678	0.3183	1.3678	1.1695
No log	30.0	90	0.6682	0.5142	0.6682	0.8175
No log	31.0	93	0.6677	0.5000	0.6677	0.8171
No log	32.0	96	0.9657	0.4201	0.9657	0.9827
No log	33.0	99	0.7032	0.5097	0.7032	0.8385
No log	34.0	102	0.8931	0.4633	0.8931	0.9450
No log	35.0	105	0.7109	0.5068	0.7109	0.8431
No log	36.0	108	0.9074	0.4696	0.9074	0.9526
No log	37.0	111	0.7254	0.4921	0.7254	0.8517
No log	38.0	114	0.9114	0.4849	0.9114	0.9547
No log	39.0	117	0.7564	0.5026	0.7564	0.8697
No log	40.0	120	0.8039	0.4770	0.8039	0.8966
No log	41.0	123	0.6981	0.5302	0.6981	0.8355
No log	42.0	126	0.7405	0.4957	0.7405	0.8605
No log	43.0	129	0.7132	0.4923	0.7132	0.8445
No log	44.0	132	0.7763	0.4899	0.7763	0.8811
No log	45.0	135	0.7122	0.5083	0.7122	0.8439
No log	46.0	138	0.9024	0.4807	0.9024	0.9499
No log	47.0	141	0.8886	0.4758	0.8886	0.9426
No log	48.0	144	0.7561	0.4909	0.7561	0.8695
No log	49.0	147	0.7845	0.4894	0.7845	0.8857
No log	50.0	150	0.6368	0.5337	0.6368	0.7980
No log	51.0	153	0.7443	0.4970	0.7443	0.8627
No log	52.0	156	0.7051	0.5199	0.7051	0.8397
No log	53.0	159	0.6151	0.5360	0.6151	0.7843
No log	54.0	162	0.7642	0.4981	0.7642	0.8742
No log	55.0	165	0.6861	0.5112	0.6861	0.8283
No log	56.0	168	0.7734	0.5137	0.7734	0.8794
No log	57.0	171	0.7924	0.4930	0.7924	0.8902
No log	58.0	174	0.7256	0.5155	0.7256	0.8518
No log	59.0	177	0.7319	0.5209	0.7319	0.8555
No log	60.0	180	0.7758	0.5146	0.7758	0.8808
No log	61.0	183	0.6781	0.5256	0.6781	0.8235
No log	62.0	186	0.6809	0.5189	0.6809	0.8252
No log	63.0	189	0.6617	0.5015	0.6617	0.8135
No log	64.0	192	0.6368	0.5204	0.6368	0.7980
No log	65.0	195	0.7417	0.5052	0.7417	0.8612
No log	66.0	198	0.6836	0.4904	0.6836	0.8268
No log	67.0	201	0.6567	0.4844	0.6567	0.8104
No log	68.0	204	0.7182	0.5064	0.7182	0.8475
No log	69.0	207	0.7257	0.5134	0.7257	0.8519
No log	70.0	210	0.6684	0.4860	0.6684	0.8176
No log	71.0	213	0.7459	0.5052	0.7459	0.8636
No log	72.0	216	0.6856	0.4977	0.6856	0.8280
No log	73.0	219	0.6617	0.4772	0.6617	0.8134

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_changed_semanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold4

ASAP_changed_semanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_changed_semanticV2_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold4