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	7.6057	0.0010	7.6059	2.7579
No log	2.0	4	6.0971	-0.0115	6.0975	2.4693
No log	3.0	6	4.9178	0.0039	4.9181	2.2177
No log	4.0	8	4.4508	0.0	4.4511	2.1098
No log	5.0	10	3.6795	0.0	3.6799	1.9183
No log	6.0	12	3.1170	0.0	3.1174	1.7656
No log	7.0	14	2.5774	0.0	2.5779	1.6056
No log	8.0	16	2.1768	0.0280	2.1772	1.4755
No log	9.0	18	1.9512	0.0280	1.9517	1.3970
No log	10.0	20	1.7601	0.0280	1.7606	1.3269
No log	11.0	22	1.4808	0.0107	1.4812	1.2171
No log	12.0	24	1.3125	0.0107	1.3130	1.1459
No log	13.0	26	1.2864	0.0174	1.2869	1.1344
No log	14.0	28	1.3609	0.0280	1.3614	1.1668
No log	15.0	30	1.2803	0.0513	1.2808	1.1317
No log	16.0	32	0.9330	0.0280	0.9334	0.9661
No log	17.0	34	1.0679	0.0118	1.0683	1.0336
No log	18.0	36	0.9504	0.0037	0.9507	0.9751
No log	19.0	38	0.8105	0.3176	0.8107	0.9004
No log	20.0	40	0.9334	0.2106	0.9338	0.9663
No log	21.0	42	0.9016	0.2895	0.9020	0.9497
No log	22.0	44	0.6333	0.4522	0.6335	0.7959
No log	23.0	46	0.6000	0.3926	0.6001	0.7747
No log	24.0	48	0.5654	0.4976	0.5655	0.7520
No log	25.0	50	0.7264	0.4614	0.7266	0.8524
No log	26.0	52	0.5435	0.5046	0.5436	0.7373
No log	27.0	54	0.5515	0.5032	0.5516	0.7427
No log	28.0	56	1.2025	0.3215	1.2031	1.0969
No log	29.0	58	1.3232	0.2901	1.3240	1.1507
No log	30.0	60	0.5565	0.5112	0.5569	0.7462
No log	31.0	62	0.5963	0.3836	0.5965	0.7723
No log	32.0	64	0.6438	0.3720	0.6439	0.8024
No log	33.0	66	0.5676	0.4271	0.5679	0.7536
No log	34.0	68	1.0642	0.3561	1.0647	1.0318
No log	35.0	70	1.3614	0.3295	1.3616	1.1669
No log	36.0	72	1.0108	0.3967	1.0108	1.0054
No log	37.0	74	0.7980	0.4443	0.7979	0.8933
No log	38.0	76	0.7177	0.4395	0.7178	0.8472
No log	39.0	78	0.7895	0.4586	0.7898	0.8887
No log	40.0	80	0.7326	0.4680	0.7329	0.8561
No log	41.0	82	0.7312	0.3800	0.7312	0.8551
No log	42.0	84	0.8257	0.3926	0.8257	0.9087
No log	43.0	86	0.8699	0.3907	0.8699	0.9327
No log	44.0	88	0.7017	0.4522	0.7017	0.8377
No log	45.0	90	0.8652	0.4284	0.8656	0.9304
No log	46.0	92	1.2072	0.3613	1.2079	1.0990
No log	47.0	94	0.7718	0.4421	0.7720	0.8787
No log	48.0	96	0.7031	0.4772	0.7029	0.8384
No log	49.0	98	0.8937	0.4001	0.8935	0.9453
No log	50.0	100	0.7943	0.4453	0.7942	0.8912
No log	51.0	102	0.6569	0.4950	0.6568	0.8104
No log	52.0	104	0.6514	0.4904	0.6514	0.8071
No log	53.0	106	0.6795	0.5207	0.6796	0.8244
No log	54.0	108	0.7173	0.5296	0.7174	0.8470
No log	55.0	110	0.7814	0.4701	0.7814	0.8840
No log	56.0	112	0.8435	0.4382	0.8436	0.9185
No log	57.0	114	0.8918	0.4404	0.8918	0.9444
No log	58.0	116	0.7848	0.4707	0.7848	0.8859
No log	59.0	118	0.7231	0.5196	0.7231	0.8504
No log	60.0	120	0.6985	0.5270	0.6986	0.8358
No log	61.0	122	0.7596	0.4860	0.7596	0.8715
No log	62.0	124	1.2538	0.3240	1.2536	1.1197
No log	63.0	126	1.4229	0.3083	1.4227	1.1928
No log	64.0	128	1.0753	0.3910	1.0751	1.0369
No log	65.0	130	0.7179	0.5103	0.7177	0.8472
No log	66.0	132	0.7173	0.5027	0.7171	0.8468
No log	67.0	134	0.9253	0.4451	0.9250	0.9618
No log	68.0	136	1.2177	0.3778	1.2174	1.1034
No log	69.0	138	1.2123	0.3803	1.2120	1.1009
No log	70.0	140	0.9418	0.4627	0.9414	0.9703
No log	71.0	142	0.6886	0.5610	0.6885	0.8297
No log	72.0	144	0.6996	0.5586	0.6995	0.8363
No log	73.0	146	0.8197	0.5106	0.8193	0.9051
No log	74.0	148	0.9356	0.5140	0.9351	0.9670
No log	75.0	150	0.8087	0.5259	0.8083	0.8990
No log	76.0	152	0.7187	0.5688	0.7186	0.8477
No log	77.0	154	0.7175	0.5677	0.7175	0.8470
No log	78.0	156	0.7128	0.5598	0.7127	0.8442
No log	79.0	158	0.7752	0.5249	0.7749	0.8803
No log	80.0	160	0.8605	0.5208	0.8602	0.9275
No log	81.0	162	0.7927	0.5305	0.7925	0.8902
No log	82.0	164	0.7416	0.5535	0.7415	0.8611
No log	83.0	166	0.8530	0.5280	0.8528	0.9235
No log	84.0	168	0.8056	0.5470	0.8055	0.8975
No log	85.0	170	0.7088	0.5639	0.7090	0.8420
No log	86.0	172	0.6849	0.5643	0.6851	0.8277
No log	87.0	174	0.7956	0.5149	0.7955	0.8919
No log	88.0	176	0.9127	0.5006	0.9125	0.9552
No log	89.0	178	0.7663	0.5370	0.7662	0.8753
No log	90.0	180	0.6773	0.5676	0.6775	0.8231
No log	91.0	182	0.6942	0.5600	0.6945	0.8334
No log	92.0	184	0.7017	0.5729	0.7018	0.8377
No log	93.0	186	0.8077	0.5642	0.8074	0.8986
No log	94.0	188	0.8333	0.5601	0.8330	0.9127
No log	95.0	190	0.7524	0.5896	0.7523	0.8673
No log	96.0	192	0.7195	0.5640	0.7198	0.8484
No log	97.0	194	0.7103	0.5687	0.7105	0.8429
No log	98.0	196	0.7504	0.5647	0.7503	0.8662
No log	99.0	198	0.7725	0.5605	0.7723	0.8788
No log	100.0	200	0.7264	0.5523	0.7264	0.8523
No log	101.0	202	0.7540	0.5523	0.7538	0.8682
No log	102.0	204	0.7160	0.5540	0.7160	0.8461
No log	103.0	206	0.6975	0.5547	0.6974	0.8351
No log	104.0	208	0.7910	0.5525	0.7908	0.8893
No log	105.0	210	0.7882	0.5481	0.7879	0.8876
No log	106.0	212	0.6799	0.5809	0.6799	0.8246
No log	107.0	214	0.6728	0.5744	0.6729	0.8203
No log	108.0	216	0.6842	0.5841	0.6843	0.8272
No log	109.0	218	0.7926	0.5560	0.7924	0.8901
No log	110.0	220	0.9363	0.5272	0.9359	0.9674
No log	111.0	222	0.9591	0.5224	0.9586	0.9791
No log	112.0	224	0.8912	0.5298	0.8908	0.9438
No log	113.0	226	0.8106	0.5505	0.8102	0.9001
No log	114.0	228	0.7443	0.5658	0.7441	0.8626
No log	115.0	230	0.6881	0.5787	0.6882	0.8296
No log	116.0	232	0.6803	0.5862	0.6805	0.8249
No log	117.0	234	0.6710	0.5750	0.6712	0.8193
No log	118.0	236	0.6555	0.5820	0.6556	0.8097
No log	119.0	238	0.6975	0.5460	0.6974	0.8351
No log	120.0	240	0.7634	0.526	0.7632	0.8736
No log	121.0	242	0.7902	0.5229	0.7899	0.8888
No log	122.0	244	0.7442	0.5397	0.7440	0.8626
No log	123.0	246	0.7136	0.5754	0.7136	0.8448
No log	124.0	248	0.7205	0.5778	0.7205	0.8488
No log	125.0	250	0.7455	0.5738	0.7454	0.8634

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

genki10/Version25NewTestASAP_FineTuningBERT_AugV25_k1_task1_organization_k1_k1_fold2

Version25NewTestASAP_FineTuningBERT_AugV25_k1_task1_organization_k1_k1_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version25NewTestASAP_FineTuningBERT_AugV25_k1_task1_organization_k1_k1_fold2