Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.125	2	4.6614	-0.0084	4.6614	2.1590
No log	0.25	4	2.5939	0.1269	2.5939	1.6106
No log	0.375	6	1.6131	0.0802	1.6131	1.2701
No log	0.5	8	1.1839	0.2236	1.1839	1.0881
No log	0.625	10	1.2201	0.3315	1.2201	1.1046
No log	0.75	12	1.8531	0.0631	1.8531	1.3613
No log	0.875	14	2.4759	0.0664	2.4759	1.5735
No log	1.0	16	2.4930	0.0159	2.4930	1.5789
No log	1.125	18	1.8138	0.1536	1.8138	1.3468
No log	1.25	20	1.3392	0.1212	1.3392	1.1572
No log	1.375	22	1.0958	0.3696	1.0958	1.0468
No log	1.5	24	1.0415	0.3696	1.0415	1.0205
No log	1.625	26	1.0520	0.4138	1.0520	1.0257
No log	1.75	28	1.1074	0.3434	1.1074	1.0523
No log	1.875	30	1.1641	0.2394	1.1641	1.0789
No log	2.0	32	1.3870	0.1117	1.3870	1.1777
No log	2.125	34	1.6211	0.1770	1.6211	1.2732
No log	2.25	36	1.7488	0.2556	1.7488	1.3224
No log	2.375	38	1.6400	0.2556	1.6400	1.2806
No log	2.5	40	1.3152	0.2789	1.3152	1.1468
No log	2.625	42	0.9957	0.4339	0.9957	0.9978
No log	2.75	44	0.7691	0.4862	0.7691	0.8770
No log	2.875	46	0.7388	0.4862	0.7388	0.8595
No log	3.0	48	0.7461	0.5206	0.7461	0.8638
No log	3.125	50	0.7263	0.5216	0.7263	0.8522
No log	3.25	52	0.7977	0.6228	0.7977	0.8932
No log	3.375	54	0.7192	0.6307	0.7192	0.8480
No log	3.5	56	0.6601	0.5882	0.6601	0.8125
No log	3.625	58	0.6408	0.6495	0.6408	0.8005
No log	3.75	60	0.7044	0.6351	0.7044	0.8393
No log	3.875	62	0.6535	0.7051	0.6535	0.8084
No log	4.0	64	0.6169	0.6824	0.6169	0.7854
No log	4.125	66	0.6224	0.7133	0.6224	0.7889
No log	4.25	68	0.6186	0.7130	0.6186	0.7865
No log	4.375	70	0.6209	0.7195	0.6209	0.7880
No log	4.5	72	0.7562	0.5549	0.7562	0.8696
No log	4.625	74	0.7773	0.5549	0.7773	0.8817
No log	4.75	76	0.6601	0.7374	0.6601	0.8125
No log	4.875	78	0.6355	0.7104	0.6355	0.7972
No log	5.0	80	0.6938	0.6654	0.6938	0.8329
No log	5.125	82	0.7149	0.6156	0.7149	0.8455
No log	5.25	84	0.7084	0.6654	0.7084	0.8417
No log	5.375	86	0.7301	0.6156	0.7301	0.8544
No log	5.5	88	0.7371	0.6156	0.7371	0.8585
No log	5.625	90	0.6546	0.6935	0.6546	0.8091
No log	5.75	92	0.6208	0.6949	0.6208	0.7879
No log	5.875	94	0.7172	0.6658	0.7172	0.8469
No log	6.0	96	0.8988	0.5476	0.8988	0.9480
No log	6.125	98	1.0384	0.5150	1.0384	1.0190
No log	6.25	100	0.9249	0.5132	0.9249	0.9617
No log	6.375	102	0.6974	0.5663	0.6974	0.8351
No log	6.5	104	0.5946	0.6518	0.5946	0.7711
No log	6.625	106	0.6651	0.6992	0.6651	0.8155
No log	6.75	108	0.7158	0.6575	0.7158	0.8460
No log	6.875	110	0.6587	0.6992	0.6587	0.8116
No log	7.0	112	0.5770	0.7247	0.5770	0.7596
No log	7.125	114	0.5625	0.7055	0.5625	0.7500
No log	7.25	116	0.5615	0.7055	0.5615	0.7494
No log	7.375	118	0.5504	0.6929	0.5504	0.7419
No log	7.5	120	0.5594	0.7374	0.5594	0.7480
No log	7.625	122	0.6039	0.712	0.6039	0.7771
No log	7.75	124	0.6796	0.6885	0.6796	0.8244
No log	7.875	126	0.6796	0.6885	0.6796	0.8244
No log	8.0	128	0.7027	0.6885	0.7027	0.8383
No log	8.125	130	0.6755	0.7008	0.6755	0.8219
No log	8.25	132	0.6236	0.7247	0.6236	0.7897
No log	8.375	134	0.5814	0.7506	0.5814	0.7625
No log	8.5	136	0.5662	0.7506	0.5662	0.7525
No log	8.625	138	0.5654	0.7506	0.5654	0.7519
No log	8.75	140	0.5679	0.7506	0.5679	0.7536
No log	8.875	142	0.5741	0.7506	0.5741	0.7577
No log	9.0	144	0.5707	0.7506	0.5707	0.7555
No log	9.125	146	0.5665	0.7506	0.5665	0.7526
No log	9.25	148	0.5629	0.7506	0.5629	0.7502
No log	9.375	150	0.5601	0.7506	0.5601	0.7484
No log	9.5	152	0.5608	0.7506	0.5608	0.7489
No log	9.625	154	0.5622	0.7506	0.5622	0.7498
No log	9.75	156	0.5615	0.7506	0.5615	0.7493
No log	9.875	158	0.5620	0.7506	0.5620	0.7496
No log	10.0	160	0.5623	0.7506	0.5623	0.7498

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/ArabicNewSplits2_FineTuningAraBERT_run4_AugV5_k3_task1_organization

ArabicNewSplits2_FineTuningAraBERT_run4_AugV5_k3_task1_organization

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
ArabicNewSplits2_FineTuningAraBERT_run4_AugV5_k3_task1_organization