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	9.7408	0.0037	9.7408	3.1210
No log	2.0	4	8.1535	0.0016	8.1535	2.8554
No log	3.0	6	5.9031	0.0443	5.9031	2.4296
No log	4.0	8	4.5903	0.0105	4.5903	2.1425
No log	5.0	10	3.6750	0.0109	3.6750	1.9170
No log	6.0	12	2.9300	0.0040	2.9300	1.7117
No log	7.0	14	2.3459	0.1388	2.3459	1.5316
No log	8.0	16	1.7922	0.0520	1.7922	1.3387
No log	9.0	18	1.5113	0.0342	1.5113	1.2293
No log	10.0	20	1.1334	0.0316	1.1334	1.0646
No log	11.0	22	0.9456	0.0316	0.9456	0.9724
No log	12.0	24	0.8487	0.3065	0.8487	0.9213
No log	13.0	26	0.7741	0.3024	0.7741	0.8798
No log	14.0	28	0.7711	0.2094	0.7711	0.8781
No log	15.0	30	0.7423	0.2533	0.7423	0.8616
No log	16.0	32	0.6907	0.2962	0.6907	0.8311
No log	17.0	34	0.6749	0.3544	0.6749	0.8215
No log	18.0	36	0.6663	0.4827	0.6663	0.8163
No log	19.0	38	0.8890	0.5051	0.8890	0.9429
No log	20.0	40	0.7992	0.5766	0.7992	0.8940
No log	21.0	42	0.8699	0.5831	0.8699	0.9327
No log	22.0	44	0.9697	0.5624	0.9697	0.9847
No log	23.0	46	0.9156	0.5775	0.9156	0.9569
No log	24.0	48	0.8928	0.6237	0.8928	0.9449
No log	25.0	50	0.8513	0.5988	0.8513	0.9226
No log	26.0	52	0.9033	0.5967	0.9033	0.9504
No log	27.0	54	1.0580	0.5768	1.0580	1.0286
No log	28.0	56	0.8431	0.6207	0.8431	0.9182
No log	29.0	58	0.5305	0.6650	0.5305	0.7283
No log	30.0	60	0.6377	0.6463	0.6377	0.7985
No log	31.0	62	0.7110	0.6501	0.7110	0.8432
No log	32.0	64	0.6715	0.6395	0.6715	0.8195
No log	33.0	66	0.7051	0.6633	0.7051	0.8397
No log	34.0	68	0.5745	0.6673	0.5745	0.7580
No log	35.0	70	0.5546	0.6665	0.5546	0.7447
No log	36.0	72	0.6240	0.6671	0.6240	0.7899
No log	37.0	74	0.7175	0.6554	0.7175	0.8470
No log	38.0	76	0.6739	0.6468	0.6739	0.8209
No log	39.0	78	0.9653	0.5799	0.9653	0.9825
No log	40.0	80	0.6674	0.6373	0.6674	0.8170
No log	41.0	82	0.6894	0.6370	0.6894	0.8303
No log	42.0	84	1.1597	0.5488	1.1597	1.0769
No log	43.0	86	1.0932	0.5545	1.0932	1.0456
No log	44.0	88	0.6925	0.6478	0.6925	0.8322
No log	45.0	90	0.6944	0.6284	0.6944	0.8333
No log	46.0	92	0.6658	0.6476	0.6658	0.8160
No log	47.0	94	0.8924	0.6001	0.8924	0.9447
No log	48.0	96	0.6810	0.6434	0.6810	0.8252
No log	49.0	98	0.6336	0.6456	0.6336	0.7960
No log	50.0	100	0.7348	0.6268	0.7348	0.8572
No log	51.0	102	0.7477	0.6423	0.7477	0.8647
No log	52.0	104	0.7466	0.6417	0.7466	0.8640
No log	53.0	106	0.7485	0.6381	0.7485	0.8652
No log	54.0	108	0.7735	0.6271	0.7735	0.8795

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold4

Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version19ASAP_FineTuningBERT_AugV19_k5_task1_organization_k5_k5_fold4