Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	10.8962	-0.0158	10.8936	3.3006
No log	2.0	4	8.3969	0.0	8.3949	2.8974
No log	3.0	6	6.7042	0.0	6.7025	2.5889
No log	4.0	8	5.4165	0.0142	5.4150	2.3270
6.9442	5.0	10	4.2677	0.0040	4.2667	2.0656
6.9442	6.0	12	3.3495	0.0	3.3486	1.8299
6.9442	7.0	14	2.8148	0.0	2.8141	1.6775
6.9442	8.0	16	2.2696	0.1862	2.2693	1.5064
6.9442	9.0	18	1.7586	0.0730	1.7584	1.3260
3.1721	10.0	20	1.5834	0.0106	1.5834	1.2583
3.1721	11.0	22	1.2131	0.0211	1.2131	1.1014
3.1721	12.0	24	1.0939	0.0521	1.0939	1.0459
3.1721	13.0	26	1.0411	0.0521	1.0411	1.0203
3.1721	14.0	28	0.9350	0.0521	0.9352	0.9670
2.0337	15.0	30	0.8613	0.1038	0.8614	0.9281
2.0337	16.0	32	0.9012	0.0914	0.9012	0.9493
2.0337	17.0	34	1.0691	0.1720	1.0690	1.0339
2.0337	18.0	36	0.8750	0.2223	0.8749	0.9354
2.0337	19.0	38	0.7441	0.3821	0.7441	0.8626
1.7083	20.0	40	0.7416	0.3785	0.7417	0.8612
1.7083	21.0	42	0.8142	0.3924	0.8141	0.9023
1.7083	22.0	44	0.6932	0.5079	0.6931	0.8325
1.7083	23.0	46	0.6251	0.4931	0.6250	0.7906
1.7083	24.0	48	0.6346	0.4782	0.6346	0.7966
1.0234	25.0	50	0.5549	0.5496	0.5548	0.7449
1.0234	26.0	52	0.5812	0.5553	0.5810	0.7623
1.0234	27.0	54	0.5452	0.5657	0.5451	0.7383
1.0234	28.0	56	0.5426	0.5095	0.5426	0.7366
1.0234	29.0	58	0.5635	0.5343	0.5635	0.7507
0.6078	30.0	60	0.6189	0.4755	0.6190	0.7867
0.6078	31.0	62	0.6736	0.4296	0.6737	0.8208
0.6078	32.0	64	0.6389	0.4995	0.6389	0.7993
0.6078	33.0	66	0.6342	0.5109	0.6342	0.7964
0.6078	34.0	68	0.7647	0.5008	0.7647	0.8745
0.4069	35.0	70	0.8560	0.4478	0.8561	0.9253
0.4069	36.0	72	0.7691	0.4905	0.7692	0.8770
0.4069	37.0	74	0.6291	0.5684	0.6289	0.7931
0.4069	38.0	76	0.6079	0.5631	0.6078	0.7796
0.4069	39.0	78	0.6862	0.5428	0.6861	0.8283
0.3522	40.0	80	0.7154	0.5268	0.7154	0.8458
0.3522	41.0	82	0.8073	0.4955	0.8073	0.8985
0.3522	42.0	84	0.7935	0.5322	0.7933	0.8907
0.3522	43.0	86	0.6491	0.5281	0.6489	0.8055
0.3522	44.0	88	0.6206	0.5462	0.6203	0.7876
0.1817	45.0	90	0.7136	0.5670	0.7133	0.8446
0.1817	46.0	92	0.7975	0.5352	0.7972	0.8929
0.1817	47.0	94	0.7510	0.5425	0.7507	0.8664
0.1817	48.0	96	0.8001	0.5287	0.7998	0.8943
0.1817	49.0	98	0.7675	0.5482	0.7672	0.8759
0.1678	50.0	100	0.6865	0.5787	0.6861	0.8283
0.1678	51.0	102	0.6757	0.5870	0.6754	0.8218
0.1678	52.0	104	0.8207	0.5395	0.8204	0.9057
0.1678	53.0	106	0.8789	0.5165	0.8786	0.9373
0.1678	54.0	108	0.9476	0.4776	0.9472	0.9733
0.1579	55.0	110	1.0389	0.4853	1.0385	1.0191
0.1579	56.0	112	0.8619	0.5370	0.8615	0.9282
0.1579	57.0	114	0.6467	0.6005	0.6463	0.8039
0.1579	58.0	116	0.6283	0.6061	0.6280	0.7924
0.1579	59.0	118	0.6679	0.5975	0.6675	0.8170
0.1597	60.0	120	0.8569	0.5571	0.8565	0.9255
0.1597	61.0	122	0.8358	0.5359	0.8354	0.9140
0.1597	62.0	124	0.9416	0.5012	0.9412	0.9702
0.1597	63.0	126	0.9721	0.4801	0.9717	0.9858
0.1597	64.0	128	1.0496	0.4720	1.0492	1.0243
0.1086	65.0	130	0.9885	0.4897	0.9881	0.9940
0.1086	66.0	132	0.9212	0.5260	0.9208	0.9596
0.1086	67.0	134	0.8490	0.5448	0.8486	0.9212
0.1086	68.0	136	0.8931	0.5527	0.8927	0.9448
0.1086	69.0	138	0.8334	0.5488	0.8330	0.9127
0.1138	70.0	140	0.7640	0.5728	0.7635	0.8738
0.1138	71.0	142	0.8857	0.5278	0.8852	0.9409
0.1138	72.0	144	0.9346	0.5101	0.9341	0.9665
0.1138	73.0	146	0.8863	0.5207	0.8858	0.9412
0.1138	74.0	148	0.9548	0.5164	0.9543	0.9769
0.0914	75.0	150	0.9679	0.5044	0.9674	0.9835
0.0914	76.0	152	0.8860	0.5174	0.8855	0.9410
0.0914	77.0	154	0.8908	0.5337	0.8903	0.9435
0.0914	78.0	156	0.8957	0.5380	0.8952	0.9462
0.0914	79.0	158	0.8573	0.5522	0.8568	0.9256
0.0779	80.0	160	0.7653	0.5697	0.7649	0.8746
0.0779	81.0	162	0.7322	0.5774	0.7317	0.8554
0.0779	82.0	164	0.7596	0.5631	0.7592	0.8713
0.0779	83.0	166	0.8765	0.5340	0.8760	0.9360
0.0779	84.0	168	0.9199	0.5120	0.9194	0.9589
0.0776	85.0	170	0.8391	0.5341	0.8386	0.9158
0.0776	86.0	172	0.7459	0.5675	0.7455	0.8634
0.0776	87.0	174	0.7455	0.5650	0.7451	0.8632
0.0776	88.0	176	0.8257	0.5418	0.8254	0.9085
0.0776	89.0	178	0.9175	0.5307	0.9171	0.9576
0.0705	90.0	180	0.9123	0.5361	0.9119	0.9549
0.0705	91.0	182	0.8482	0.5397	0.8478	0.9208
0.0705	92.0	184	0.7898	0.5576	0.7894	0.8885
0.0705	93.0	186	0.7829	0.5609	0.7826	0.8846
0.0705	94.0	188	0.8112	0.5530	0.8108	0.9004
0.0733	95.0	190	0.8611	0.5376	0.8607	0.9278
0.0733	96.0	192	0.8908	0.5325	0.8904	0.9436
0.0733	97.0	194	0.9063	0.5284	0.9059	0.9518
0.0733	98.0	196	0.9142	0.5281	0.9138	0.9559
0.0733	99.0	198	0.9126	0.5281	0.9122	0.9551
0.0712	100.0	200	0.9096	0.5281	0.9092	0.9535

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1

genki10/ASAP_FineTuningBERT_AugV6_k1_task1_organization_fold1

ASAP_FineTuningBERT_AugV6_k1_task1_organization_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
ASAP_FineTuningBERT_AugV6_k1_task1_organization_fold1