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	10.7994	0.0040	10.7994	3.2862
No log	2.0	4	9.6653	0.0	9.6653	3.1089
No log	3.0	6	9.0019	0.0	9.0019	3.0003
No log	4.0	8	8.2204	0.0	8.2204	2.8671
No log	5.0	10	7.4584	0.0	7.4584	2.7310
No log	6.0	12	6.7246	0.0	6.7246	2.5932
No log	7.0	14	5.9668	0.0057	5.9668	2.4427
No log	8.0	16	5.0912	0.0079	5.0912	2.2564
No log	9.0	18	4.1309	0.0040	4.1309	2.0325
No log	10.0	20	3.3352	0.0040	3.3352	1.8263
No log	11.0	22	2.6587	0.0040	2.6587	1.6305
No log	12.0	24	2.1772	0.1499	2.1772	1.4755
No log	13.0	26	1.9365	0.0213	1.9365	1.3916
No log	14.0	28	1.5685	0.0213	1.5685	1.2524
No log	15.0	30	1.2435	0.0316	1.2435	1.1151
No log	16.0	32	1.1926	0.0870	1.1926	1.0921
No log	17.0	34	0.9599	0.0710	0.9599	0.9798
No log	18.0	36	0.9523	0.0710	0.9523	0.9759
No log	19.0	38	0.8816	0.1374	0.8816	0.9389
No log	20.0	40	1.4135	0.2268	1.4135	1.1889
No log	21.0	42	1.5828	0.2462	1.5828	1.2581
No log	22.0	44	0.8910	0.2523	0.8910	0.9439
No log	23.0	46	0.8590	0.2253	0.8590	0.9268
No log	24.0	48	1.1816	0.2613	1.1816	1.0870
No log	25.0	50	1.5466	0.2722	1.5466	1.2436
No log	26.0	52	1.0782	0.3416	1.0782	1.0384
No log	27.0	54	0.8455	0.4866	0.8455	0.9195
No log	28.0	56	1.5846	0.3104	1.5846	1.2588
No log	29.0	58	1.7200	0.2874	1.7200	1.3115
No log	30.0	60	0.9430	0.4478	0.9430	0.9711
No log	31.0	62	0.9896	0.4315	0.9896	0.9948
No log	32.0	64	1.2514	0.3526	1.2514	1.1186
No log	33.0	66	0.9024	0.4432	0.9024	0.9499
No log	34.0	68	0.9316	0.4449	0.9316	0.9652
No log	35.0	70	1.3897	0.3278	1.3897	1.1788
No log	36.0	72	1.1953	0.3974	1.1953	1.0933
No log	37.0	74	1.2957	0.3580	1.2957	1.1383
No log	38.0	76	1.7290	0.2708	1.7290	1.3149
No log	39.0	78	1.5188	0.3151	1.5188	1.2324
No log	40.0	80	1.2947	0.3792	1.2947	1.1378
No log	41.0	82	1.3826	0.3544	1.3826	1.1758
No log	42.0	84	1.6676	0.2969	1.6676	1.2913
No log	43.0	86	1.1487	0.4465	1.1487	1.0718
No log	44.0	88	1.1803	0.4393	1.1803	1.0864
No log	45.0	90	1.5725	0.3157	1.5725	1.2540
No log	46.0	92	1.4494	0.3474	1.4494	1.2039
No log	47.0	94	1.3859	0.3707	1.3859	1.1772

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV17_k1_task1_organization_k1_k1_fold4

ASAP_FineTuningBERT_AugV17_k1_task1_organization_k1_k1_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV17_k1_task1_organization_k1_k1_fold4