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	1	11.0699	0.0144	11.0699	3.3271
No log	2.0	2	10.8128	-0.0005	10.8128	3.2883
No log	3.0	3	9.1009	0.0	9.1009	3.0168
No log	4.0	4	8.1600	0.0	8.1600	2.8566
No log	5.0	5	7.3523	0.0	7.3523	2.7115
No log	6.0	6	6.3941	0.0113	6.3941	2.5286
No log	7.0	7	5.8471	0.0311	5.8471	2.4181
No log	8.0	8	5.2663	0.0235	5.2663	2.2948
No log	9.0	9	4.2833	0.0170	4.2833	2.0696
No log	10.0	10	3.7512	0.0115	3.7512	1.9368
No log	11.0	11	3.1905	0.0115	3.1905	1.7862
No log	12.0	12	2.6853	0.0156	2.6853	1.6387
No log	13.0	13	2.3643	0.1477	2.3643	1.5376
No log	14.0	14	2.1132	0.1147	2.1132	1.4537
No log	15.0	15	1.8688	0.0750	1.8688	1.3671
No log	16.0	16	1.6640	0.0426	1.6640	1.2900
No log	17.0	17	1.4334	0.0344	1.4334	1.1973
No log	18.0	18	1.2543	0.0344	1.2543	1.1199
No log	19.0	19	1.1256	0.0344	1.1256	1.0609
No log	20.0	20	1.0273	0.0344	1.0273	1.0135
No log	21.0	21	0.9404	0.0344	0.9404	0.9697
No log	22.0	22	0.8583	0.2572	0.8583	0.9265
No log	23.0	23	0.7956	0.3456	0.7956	0.8920
No log	24.0	24	0.7618	0.3064	0.7618	0.8728
No log	25.0	25	0.7114	0.3003	0.7114	0.8435
No log	26.0	26	0.6809	0.2960	0.6809	0.8252
No log	27.0	27	0.6832	0.3248	0.6832	0.8266
No log	28.0	28	0.6764	0.3436	0.6764	0.8224
No log	29.0	29	0.6675	0.3172	0.6675	0.8170
No log	30.0	30	0.6937	0.3069	0.6937	0.8329
No log	31.0	31	0.6799	0.3413	0.6799	0.8245
No log	32.0	32	0.6900	0.3778	0.6900	0.8307
No log	33.0	33	0.6959	0.3809	0.6959	0.8342
No log	34.0	34	0.6784	0.3635	0.6784	0.8237
No log	35.0	35	0.7539	0.3191	0.7539	0.8683
No log	36.0	36	0.7962	0.3558	0.7962	0.8923
No log	37.0	37	0.7859	0.3531	0.7859	0.8865
No log	38.0	38	0.7748	0.3703	0.7748	0.8802
No log	39.0	39	0.7882	0.3830	0.7882	0.8878
No log	40.0	40	0.8326	0.3737	0.8326	0.9125
No log	41.0	41	0.9042	0.3715	0.9042	0.9509
No log	42.0	42	0.9208	0.3783	0.9208	0.9596
No log	43.0	43	0.8407	0.3922	0.8407	0.9169
No log	44.0	44	0.8053	0.4312	0.8053	0.8974
No log	45.0	45	0.8273	0.4283	0.8273	0.9096
No log	46.0	46	0.8788	0.4109	0.8788	0.9374
No log	47.0	47	0.8538	0.4144	0.8538	0.9240
No log	48.0	48	0.7892	0.4050	0.7892	0.8884
No log	49.0	49	0.7888	0.3988	0.7888	0.8882
No log	50.0	50	0.8250	0.4079	0.8250	0.9083
No log	51.0	51	0.8933	0.3945	0.8933	0.9451
No log	52.0	52	0.8985	0.3931	0.8985	0.9479
No log	53.0	53	0.8436	0.3932	0.8436	0.9185
No log	54.0	54	0.8311	0.3959	0.8311	0.9117
No log	55.0	55	0.8575	0.3855	0.8575	0.9260
No log	56.0	56	0.9335	0.3674	0.9335	0.9662
No log	57.0	57	0.9709	0.3872	0.9709	0.9853
No log	58.0	58	0.9356	0.3622	0.9356	0.9673
No log	59.0	59	0.8946	0.3601	0.8946	0.9458
No log	60.0	60	0.8810	0.3573	0.8810	0.9386
No log	61.0	61	0.9013	0.3590	0.9013	0.9494
No log	62.0	62	0.9613	0.3366	0.9613	0.9805
No log	63.0	63	1.0748	0.3803	1.0748	1.0367
No log	64.0	64	1.1446	0.3660	1.1446	1.0698
No log	65.0	65	1.1237	0.3744	1.1237	1.0600
No log	66.0	66	1.0416	0.3760	1.0416	1.0206
No log	67.0	67	0.9477	0.3445	0.9477	0.9735
No log	68.0	68	0.9240	0.3484	0.9240	0.9612
No log	69.0	69	0.9183	0.3435	0.9183	0.9583
No log	70.0	70	0.9338	0.3497	0.9338	0.9663
No log	71.0	71	0.9897	0.3563	0.9897	0.9948
No log	72.0	72	1.0990	0.3798	1.0990	1.0483
No log	73.0	73	1.1596	0.3664	1.1596	1.0768
No log	74.0	74	1.1540	0.3669	1.1540	1.0742

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Trial3BERT_AugV8_k1_task1_organization_k1_fold0

Trial3BERT_AugV8_k1_task1_organization_k1_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Trial3BERT_AugV8_k1_task1_organization_k1_fold0