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	8.0416	0.0	8.0416	2.8358
No log	2.0	8	6.2627	0.0180	6.2627	2.5025
No log	3.0	12	4.5395	0.0	4.5395	2.1306
No log	4.0	16	2.9594	0.0	2.9594	1.7203
No log	5.0	20	1.8189	0.0	1.8189	1.3486
No log	6.0	24	1.7649	0.0	1.7649	1.3285
No log	7.0	28	2.3012	0.1749	2.3012	1.5170
No log	8.0	32	1.3798	0.0133	1.3798	1.1747
No log	9.0	36	1.8099	0.1627	1.8099	1.3453
No log	10.0	40	1.0038	0.2002	1.0038	1.0019
No log	11.0	44	0.8491	0.3571	0.8491	0.9215
No log	12.0	48	0.8628	0.3371	0.8628	0.9289
No log	13.0	52	1.2336	0.3059	1.2336	1.1107
No log	14.0	56	0.6891	0.2527	0.6891	0.8301
No log	15.0	60	1.1796	0.3020	1.1796	1.0861
No log	16.0	64	0.8686	0.4297	0.8686	0.9320
No log	17.0	68	0.8208	0.4093	0.8208	0.9060
No log	18.0	72	0.7645	0.4650	0.7645	0.8744
No log	19.0	76	0.7268	0.4526	0.7268	0.8525
No log	20.0	80	0.6895	0.4679	0.6895	0.8303
No log	21.0	84	0.7262	0.4713	0.7262	0.8522
No log	22.0	88	0.8452	0.4464	0.8452	0.9193
No log	23.0	92	0.7376	0.4580	0.7376	0.8589
No log	24.0	96	1.0852	0.3798	1.0852	1.0417
No log	25.0	100	0.7169	0.5247	0.7169	0.8467
No log	26.0	104	0.7189	0.4590	0.7189	0.8479
No log	27.0	108	0.7796	0.4116	0.7796	0.8830
No log	28.0	112	0.7024	0.5206	0.7024	0.8381
No log	29.0	116	0.6832	0.5271	0.6832	0.8266
No log	30.0	120	0.7268	0.4542	0.7268	0.8525
No log	31.0	124	0.7020	0.5094	0.7020	0.8379
No log	32.0	128	0.6939	0.4289	0.6939	0.8330
No log	33.0	132	0.6806	0.5188	0.6806	0.8250
No log	34.0	136	0.7851	0.4410	0.7851	0.8861
No log	35.0	140	0.7338	0.4099	0.7338	0.8566
No log	36.0	144	0.7224	0.5252	0.7224	0.8499
No log	37.0	148	0.7764	0.4400	0.7764	0.8812
No log	38.0	152	0.6881	0.4380	0.6881	0.8295
No log	39.0	156	0.7698	0.4655	0.7698	0.8774
No log	40.0	160	0.7452	0.4103	0.7452	0.8633
No log	41.0	164	0.7113	0.4003	0.7113	0.8434
No log	42.0	168	0.8208	0.4398	0.8208	0.9060
No log	43.0	172	0.6884	0.4697	0.6884	0.8297
No log	44.0	176	0.7796	0.4375	0.7796	0.8830
No log	45.0	180	0.6965	0.4535	0.6965	0.8345
No log	46.0	184	0.7030	0.4399	0.7030	0.8385
No log	47.0	188	0.7097	0.5040	0.7097	0.8425
No log	48.0	192	0.7328	0.4063	0.7328	0.8560
No log	49.0	196	0.7068	0.4305	0.7068	0.8407

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version12NewTestASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

Version12NewTestASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version12NewTestASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0