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	9.6564	0.0028	9.6540	3.1071
No log	2.0	4	6.5923	0.0	6.5898	2.5671
No log	3.0	6	5.0188	0.0161	5.0169	2.2398
No log	4.0	8	3.9354	0.0	3.9334	1.9833
No log	5.0	10	3.1854	0.0	3.1835	1.7842
No log	6.0	12	2.6126	0.0	2.6107	1.6158
No log	7.0	14	1.8929	0.0315	1.8912	1.3752
No log	8.0	16	1.3489	0.0	1.3474	1.1608
No log	9.0	18	1.0666	0.0	1.0652	1.0321
No log	10.0	20	0.9426	0.0	0.9413	0.9702
No log	11.0	22	0.8612	0.3277	0.8601	0.9274
No log	12.0	24	0.8233	0.3287	0.8220	0.9067
No log	13.0	26	1.1488	0.1027	1.1474	1.0712
No log	14.0	28	0.8163	0.2548	0.8150	0.9028
No log	15.0	30	0.7408	0.4309	0.7397	0.8600
No log	16.0	32	0.8101	0.2318	0.8089	0.8994
No log	17.0	34	0.7048	0.4735	0.7037	0.8389
No log	18.0	36	0.7277	0.5230	0.7265	0.8524
No log	19.0	38	0.8606	0.4855	0.8593	0.9270
No log	20.0	40	0.6467	0.5695	0.6455	0.8034
No log	21.0	42	0.5670	0.5971	0.5659	0.7522
No log	22.0	44	0.5733	0.5883	0.5721	0.7564
No log	23.0	46	0.7174	0.5443	0.7161	0.8462
No log	24.0	48	0.6177	0.5795	0.6164	0.7851
No log	25.0	50	0.6313	0.4757	0.6303	0.7939
No log	26.0	52	0.6241	0.4617	0.6231	0.7893
No log	27.0	54	0.6375	0.5692	0.6362	0.7976
No log	28.0	56	0.7381	0.5252	0.7368	0.8583
No log	29.0	58	0.5301	0.5364	0.5291	0.7274
No log	30.0	60	0.6946	0.4167	0.6937	0.8329
No log	31.0	62	0.5630	0.5324	0.5620	0.7497
No log	32.0	64	0.6202	0.5623	0.6188	0.7866
No log	33.0	66	0.5396	0.5910	0.5384	0.7337
No log	34.0	68	0.5971	0.5720	0.5962	0.7721
No log	35.0	70	0.5480	0.6041	0.5470	0.7396
No log	36.0	72	0.6154	0.5875	0.6140	0.7836
No log	37.0	74	0.6423	0.5753	0.6408	0.8005
No log	38.0	76	0.5629	0.5862	0.5617	0.7494
No log	39.0	78	0.8107	0.4769	0.8098	0.8999
No log	40.0	80	0.6770	0.5781	0.6761	0.8223
No log	41.0	82	0.5332	0.6260	0.5321	0.7294
No log	42.0	84	0.5327	0.6306	0.5314	0.7290
No log	43.0	86	0.5788	0.6353	0.5777	0.7601
No log	44.0	88	0.6907	0.5295	0.6897	0.8305
No log	45.0	90	0.6037	0.6043	0.6027	0.7763
No log	46.0	92	0.5082	0.6493	0.5070	0.7120
No log	47.0	94	0.5108	0.6454	0.5096	0.7138
No log	48.0	96	0.5196	0.6442	0.5184	0.7200
No log	49.0	98	0.7845	0.4997	0.7836	0.8852
No log	50.0	100	0.7462	0.5029	0.7452	0.8633
No log	51.0	102	0.5566	0.6335	0.5554	0.7452
No log	52.0	104	0.5223	0.6619	0.5211	0.7219
No log	53.0	106	0.5616	0.6389	0.5605	0.7486
No log	54.0	108	0.5872	0.6502	0.5861	0.7656
No log	55.0	110	0.6530	0.5803	0.6518	0.8074
No log	56.0	112	0.6360	0.5950	0.6348	0.7968
No log	57.0	114	0.5415	0.6600	0.5402	0.7349
No log	58.0	116	0.6087	0.6404	0.6076	0.7795
No log	59.0	118	0.6060	0.6499	0.6049	0.7777
No log	60.0	120	0.5459	0.6712	0.5446	0.7380
No log	61.0	122	0.5655	0.6564	0.5643	0.7512
No log	62.0	124	0.7632	0.5598	0.7622	0.8730
No log	63.0	126	0.7022	0.5640	0.7011	0.8373
No log	64.0	128	0.5817	0.6422	0.5804	0.7619
No log	65.0	130	0.6477	0.6053	0.6466	0.8041
No log	66.0	132	0.8170	0.5591	0.8161	0.9034
No log	67.0	134	0.7033	0.5839	0.7024	0.8381
No log	68.0	136	0.5359	0.6560	0.5348	0.7313
No log	69.0	138	0.5189	0.6696	0.5176	0.7194
No log	70.0	140	0.5190	0.6738	0.5177	0.7195
No log	71.0	142	0.5593	0.6538	0.5582	0.7471
No log	72.0	144	0.7598	0.5581	0.7588	0.8711
No log	73.0	146	0.7118	0.5736	0.7108	0.8431
No log	74.0	148	0.5352	0.6607	0.5340	0.7308
No log	75.0	150	0.5203	0.6657	0.5191	0.7205
No log	76.0	152	0.5241	0.6669	0.5229	0.7231
No log	77.0	154	0.5478	0.6527	0.5467	0.7394
No log	78.0	156	0.5748	0.6370	0.5737	0.7574
No log	79.0	158	0.5894	0.6283	0.5883	0.7670
No log	80.0	160	0.6282	0.6011	0.6271	0.7919
No log	81.0	162	0.7007	0.5746	0.6997	0.8365
No log	82.0	164	0.6579	0.5828	0.6569	0.8105
No log	83.0	166	0.5627	0.6393	0.5615	0.7493
No log	84.0	168	0.5438	0.6616	0.5426	0.7366
No log	85.0	170	0.5681	0.6372	0.5670	0.7530
No log	86.0	172	0.6360	0.5925	0.6350	0.7969
No log	87.0	174	0.6464	0.5810	0.6454	0.8034
No log	88.0	176	0.6033	0.6134	0.6023	0.7761
No log	89.0	178	0.5623	0.6541	0.5612	0.7491
No log	90.0	180	0.5346	0.6687	0.5334	0.7304

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold1

Version3ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3ASAP_FineTuningBERT_AugV14_k1_task1_organization_k1_k1_fold1