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	5	7.1418	0.0	7.1418	2.6724
No log	2.0	10	5.0267	0.0115	5.0267	2.2420
No log	3.0	15	2.9832	0.0	2.9832	1.7272
No log	4.0	20	1.5950	0.0316	1.5950	1.2629
No log	5.0	25	1.5728	0.0737	1.5728	1.2541
No log	6.0	30	0.9522	0.0548	0.9522	0.9758
No log	7.0	35	1.0125	0.2177	1.0125	1.0062
No log	8.0	40	0.7873	0.4086	0.7873	0.8873
No log	9.0	45	0.7480	0.4270	0.7480	0.8649
No log	10.0	50	0.6555	0.4011	0.6555	0.8096
No log	11.0	55	0.6690	0.3847	0.6690	0.8179
No log	12.0	60	0.7284	0.4517	0.7284	0.8535
No log	13.0	65	0.7623	0.4650	0.7623	0.8731
No log	14.0	70	0.7871	0.4417	0.7871	0.8872
No log	15.0	75	1.0726	0.3662	1.0726	1.0356
No log	16.0	80	0.6959	0.4854	0.6959	0.8342
No log	17.0	85	0.7220	0.4758	0.7220	0.8497
No log	18.0	90	0.6874	0.4470	0.6874	0.8291
No log	19.0	95	0.8048	0.4251	0.8048	0.8971
No log	20.0	100	0.8516	0.4331	0.8516	0.9228
No log	21.0	105	0.7213	0.4793	0.7213	0.8493
No log	22.0	110	0.7221	0.4798	0.7221	0.8498
No log	23.0	115	0.6934	0.4242	0.6934	0.8327
No log	24.0	120	0.7188	0.4701	0.7188	0.8478
No log	25.0	125	0.7199	0.4657	0.7199	0.8485
No log	26.0	130	0.8633	0.4396	0.8633	0.9291
No log	27.0	135	0.6985	0.4965	0.6985	0.8358
No log	28.0	140	0.6791	0.4814	0.6791	0.8241
No log	29.0	145	0.6548	0.4767	0.6548	0.8092
No log	30.0	150	0.6791	0.4652	0.6791	0.8241
No log	31.0	155	0.7233	0.4407	0.7233	0.8505
No log	32.0	160	0.6625	0.4970	0.6625	0.8139
No log	33.0	165	0.6203	0.4694	0.6203	0.7876
No log	34.0	170	0.7061	0.4544	0.7061	0.8403
No log	35.0	175	0.6358	0.5019	0.6358	0.7973
No log	36.0	180	0.6514	0.5301	0.6514	0.8071
No log	37.0	185	0.6245	0.5215	0.6245	0.7903
No log	38.0	190	0.6685	0.5107	0.6685	0.8176
No log	39.0	195	0.6227	0.5365	0.6227	0.7891
No log	40.0	200	0.6214	0.5197	0.6214	0.7883
No log	41.0	205	0.6298	0.5054	0.6298	0.7936
No log	42.0	210	0.7992	0.4237	0.7992	0.8940
No log	43.0	215	0.6321	0.5009	0.6321	0.7950
No log	44.0	220	0.6022	0.5001	0.6022	0.7760
No log	45.0	225	0.7049	0.4627	0.7049	0.8396
No log	46.0	230	0.6239	0.5134	0.6239	0.7899
No log	47.0	235	0.6129	0.5161	0.6129	0.7829
No log	48.0	240	0.6625	0.5176	0.6625	0.8139
No log	49.0	245	0.6595	0.5000	0.6595	0.8121
No log	50.0	250	0.6812	0.4708	0.6812	0.8254
No log	51.0	255	0.6339	0.5242	0.6339	0.7962
No log	52.0	260	0.7493	0.4642	0.7493	0.8656
No log	53.0	265	0.6413	0.5023	0.6413	0.8008
No log	54.0	270	0.6099	0.5091	0.6099	0.7809
No log	55.0	275	0.6227	0.5022	0.6227	0.7891
No log	56.0	280	0.6273	0.5077	0.6273	0.7920
No log	57.0	285	0.6875	0.5002	0.6875	0.8292
No log	58.0	290	0.5782	0.5115	0.5782	0.7604
No log	59.0	295	0.5772	0.5017	0.5772	0.7597
No log	60.0	300	0.6129	0.5015	0.6129	0.7829
No log	61.0	305	0.6115	0.5308	0.6115	0.7820
No log	62.0	310	0.6287	0.5389	0.6287	0.7929
No log	63.0	315	0.6224	0.5153	0.6224	0.7889
No log	64.0	320	0.6152	0.5034	0.6152	0.7844
No log	65.0	325	0.6205	0.5126	0.6205	0.7877
No log	66.0	330	0.6673	0.4794	0.6673	0.8169
No log	67.0	335	0.6113	0.5180	0.6113	0.7819
No log	68.0	340	0.6022	0.5109	0.6022	0.7760
No log	69.0	345	0.6431	0.5015	0.6431	0.8019
No log	70.0	350	0.6086	0.5330	0.6086	0.7801
No log	71.0	355	0.6332	0.5084	0.6332	0.7957
No log	72.0	360	0.6155	0.5378	0.6155	0.7845
No log	73.0	365	0.6208	0.4992	0.6208	0.7879
No log	74.0	370	0.6154	0.5068	0.6154	0.7845
No log	75.0	375	0.6112	0.5118	0.6112	0.7818
No log	76.0	380	0.6232	0.4921	0.6232	0.7894
No log	77.0	385	0.6035	0.5115	0.6035	0.7768
No log	78.0	390	0.5959	0.5122	0.5959	0.7720
No log	79.0	395	0.6019	0.4973	0.6019	0.7758
No log	80.0	400	0.6033	0.5265	0.6033	0.7767
No log	81.0	405	0.6146	0.4966	0.6146	0.7840
No log	82.0	410	0.6096	0.5031	0.6096	0.7807
No log	83.0	415	0.6348	0.4973	0.6348	0.7967
No log	84.0	420	0.6129	0.5172	0.6129	0.7829
No log	85.0	425	0.6247	0.5136	0.6247	0.7904
No log	86.0	430	0.6033	0.5230	0.6033	0.7767
No log	87.0	435	0.6112	0.5142	0.6112	0.7818
No log	88.0	440	0.6014	0.5209	0.6014	0.7755
No log	89.0	445	0.5996	0.5160	0.5996	0.7743
No log	90.0	450	0.6151	0.5074	0.6151	0.7843
No log	91.0	455	0.5962	0.5232	0.5962	0.7721
No log	92.0	460	0.5976	0.5132	0.5976	0.7731

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/ASAP_FineTuningBERT_AugV21_k5_task1_organization_k5_k5_fold0

ASAP_FineTuningBERT_AugV21_k5_task1_organization_k5_k5_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV21_k5_task1_organization_k5_k5_fold0