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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	8.9813	0.0	8.9813	2.9969
No log	2.0	4	7.5918	0.0	7.5918	2.7553
No log	3.0	6	6.8033	0.0	6.8033	2.6083
No log	4.0	8	5.9072	0.0216	5.9072	2.4305
No log	5.0	10	5.0443	0.0115	5.0443	2.2459
No log	6.0	12	4.2446	0.0039	4.2446	2.0603
No log	7.0	14	3.4352	0.0	3.4352	1.8534
No log	8.0	16	2.7039	0.0	2.7039	1.6444
No log	9.0	18	2.0531	0.0689	2.0531	1.4329
No log	10.0	20	1.5662	0.0316	1.5662	1.2515
No log	11.0	22	1.2475	0.0316	1.2475	1.1169
No log	12.0	24	1.0150	0.0316	1.0150	1.0075
No log	13.0	26	0.8152	0.4249	0.8152	0.9029
No log	14.0	28	0.7176	0.4805	0.7176	0.8471
No log	15.0	30	0.8142	0.3358	0.8142	0.9024
No log	16.0	32	0.6018	0.4590	0.6018	0.7758
No log	17.0	34	0.8426	0.4216	0.8426	0.9179
No log	18.0	36	0.8378	0.4104	0.8378	0.9153
No log	19.0	38	0.5595	0.4802	0.5595	0.7480
No log	20.0	40	0.8279	0.4261	0.8279	0.9099
No log	21.0	42	0.7702	0.4464	0.7702	0.8776
No log	22.0	44	0.5680	0.4803	0.5680	0.7536
No log	23.0	46	0.7489	0.4426	0.7489	0.8654
No log	24.0	48	0.6287	0.4502	0.6287	0.7929
No log	25.0	50	0.6345	0.4495	0.6345	0.7966
No log	26.0	52	0.6769	0.4605	0.6769	0.8227
No log	27.0	54	0.6554	0.4608	0.6554	0.8096
No log	28.0	56	0.6399	0.4806	0.6399	0.7999
No log	29.0	58	0.6411	0.5155	0.6411	0.8007
No log	30.0	60	0.7111	0.4568	0.7111	0.8433
No log	31.0	62	0.6771	0.5074	0.6771	0.8229
No log	32.0	64	0.6864	0.4957	0.6864	0.8285
No log	33.0	66	0.6248	0.5159	0.6248	0.7904
No log	34.0	68	0.6731	0.5226	0.6731	0.8204
No log	35.0	70	0.5927	0.5683	0.5927	0.7699
No log	36.0	72	0.6161	0.5250	0.6161	0.7849
No log	37.0	74	0.6097	0.5450	0.6097	0.7809
No log	38.0	76	0.5878	0.5130	0.5878	0.7667
No log	39.0	78	0.6254	0.5416	0.6254	0.7908
No log	40.0	80	0.6756	0.5137	0.6756	0.8220
No log	41.0	82	0.6373	0.5442	0.6373	0.7983
No log	42.0	84	0.5896	0.5319	0.5896	0.7679
No log	43.0	86	0.5894	0.5019	0.5894	0.7677
No log	44.0	88	0.5993	0.5628	0.5993	0.7741
No log	45.0	90	0.6266	0.4827	0.6266	0.7916
No log	46.0	92	0.6119	0.5110	0.6119	0.7823
No log	47.0	94	0.6774	0.5461	0.6774	0.8231
No log	48.0	96	0.6211	0.5181	0.6211	0.7881
No log	49.0	98	0.6148	0.5220	0.6148	0.7841
No log	50.0	100	0.7058	0.5391	0.7058	0.8401
No log	51.0	102	0.5967	0.5340	0.5967	0.7725
No log	52.0	104	0.6078	0.5677	0.6078	0.7796
No log	53.0	106	0.7269	0.5224	0.7269	0.8526
No log	54.0	108	0.6180	0.5443	0.6180	0.7862
No log	55.0	110	0.6305	0.5259	0.6305	0.7940
No log	56.0	112	0.8128	0.5070	0.8128	0.9015
No log	57.0	114	0.8286	0.5027	0.8286	0.9103
No log	58.0	116	0.5743	0.5313	0.5743	0.7578
No log	59.0	118	0.5865	0.5168	0.5865	0.7658
No log	60.0	120	0.6327	0.5569	0.6327	0.7954
No log	61.0	122	0.6664	0.5389	0.6664	0.8163
No log	62.0	124	0.5986	0.5086	0.5986	0.7737
No log	63.0	126	0.6039	0.5221	0.6039	0.7771
No log	64.0	128	0.6708	0.5280	0.6708	0.8190
No log	65.0	130	0.6003	0.5294	0.6003	0.7748

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version23NewTestASAP_FineTuningBERT_AugV23_k3_task1_organization_k3_k3_fold0

Version23NewTestASAP_FineTuningBERT_AugV23_k3_task1_organization_k3_k3_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version23NewTestASAP_FineTuningBERT_AugV23_k3_task1_organization_k3_k3_fold0