Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1111	2	4.6306	-0.0619	4.6306	2.1519
No log	0.2222	4	2.4530	-0.0491	2.4530	1.5662
No log	0.3333	6	1.4149	0.0556	1.4149	1.1895
No log	0.4444	8	0.7893	-0.1613	0.7893	0.8884
No log	0.5556	10	1.1922	-0.2000	1.1922	1.0919
No log	0.6667	12	1.0490	-0.0952	1.0490	1.0242
No log	0.7778	14	0.7731	0.1724	0.7731	0.8793
No log	0.8889	16	0.5634	0.0426	0.5634	0.7506
No log	1.0	18	0.6301	0.0	0.6301	0.7938
No log	1.1111	20	0.7285	0.1000	0.7285	0.8536
No log	1.2222	22	0.6307	-0.0385	0.6307	0.7942
No log	1.3333	24	0.6218	-0.0364	0.6218	0.7885
No log	1.4444	26	0.6394	-0.0345	0.6394	0.7996
No log	1.5556	28	0.7696	0.1563	0.7696	0.8772
No log	1.6667	30	0.7265	0.1905	0.7265	0.8523
No log	1.7778	32	0.6666	0.2623	0.6666	0.8165
No log	1.8889	34	0.6155	-0.0714	0.6155	0.7845
No log	2.0	36	0.5932	0.0727	0.5932	0.7702
No log	2.1111	38	0.6625	0.0690	0.6625	0.8139
No log	2.2222	40	0.7183	0.0	0.7183	0.8475
No log	2.3333	42	0.5916	0.1509	0.5916	0.7692
No log	2.4444	44	0.6131	0.1600	0.6131	0.7830
No log	2.5556	46	0.6434	0.1923	0.6434	0.8021
No log	2.6667	48	0.6817	0.1176	0.6817	0.8256
No log	2.7778	50	0.7013	-0.1176	0.7013	0.8374
No log	2.8889	52	0.6859	-0.0385	0.6859	0.8282
No log	3.0	54	0.6619	0.1176	0.6619	0.8136
No log	3.1111	56	0.6579	0.0377	0.6579	0.8111
No log	3.2222	58	0.6878	0.1290	0.6878	0.8293
No log	3.3333	60	0.6630	0.1111	0.6630	0.8142
No log	3.4444	62	0.6548	0.1111	0.6548	0.8092
No log	3.5556	64	0.6557	0.1176	0.6557	0.8098
No log	3.6667	66	0.6959	0.1429	0.6959	0.8342
No log	3.7778	68	0.6999	0.1429	0.6999	0.8366
No log	3.8889	70	0.6792	0.0	0.6792	0.8241
No log	4.0	72	0.6667	0.1231	0.6667	0.8165
No log	4.1111	74	0.6607	0.0909	0.6607	0.8128
No log	4.2222	76	0.6203	0.2105	0.6203	0.7876
No log	4.3333	78	0.5875	0.1176	0.5875	0.7665
No log	4.4444	80	0.5553	0.2353	0.5553	0.7452
No log	4.5556	82	0.5382	0.2500	0.5382	0.7336
No log	4.6667	84	0.5298	0.2623	0.5298	0.7278
No log	4.7778	86	0.5405	0.2258	0.5405	0.7352
No log	4.8889	88	0.5465	0.2623	0.5465	0.7392
No log	5.0	90	0.5666	0.2105	0.5666	0.7527
No log	5.1111	92	0.6204	0.2154	0.6204	0.7877
No log	5.2222	94	0.6334	0.1818	0.6334	0.7959
No log	5.3333	96	0.6308	0.2388	0.6308	0.7942
No log	5.4444	98	0.6537	0.1176	0.6537	0.8085
No log	5.5556	100	0.6593	0.25	0.6593	0.8119
No log	5.6667	102	0.6645	0.3014	0.6645	0.8152
No log	5.7778	104	0.6684	0.2105	0.6684	0.8175
No log	5.8889	106	0.6744	0.2222	0.6744	0.8212
No log	6.0	108	0.6782	0.3077	0.6782	0.8235
No log	6.1111	110	0.7073	0.3014	0.7073	0.8410
No log	6.2222	112	0.7157	0.3077	0.7157	0.8460
No log	6.3333	114	0.7371	0.3250	0.7371	0.8585
No log	6.4444	116	0.7651	0.3250	0.7651	0.8747
No log	6.5556	118	0.7784	0.2222	0.7784	0.8822
No log	6.6667	120	0.7888	0.3077	0.7888	0.8881
No log	6.7778	122	0.7838	0.3077	0.7838	0.8853
No log	6.8889	124	0.7682	0.2105	0.7682	0.8765
No log	7.0	126	0.7723	0.2222	0.7723	0.8788
No log	7.1111	128	0.7909	0.2222	0.7909	0.8893
No log	7.2222	130	0.8115	0.1750	0.8115	0.9008
No log	7.3333	132	0.8222	0.1750	0.8222	0.9068
No log	7.4444	134	0.8201	0.2683	0.8201	0.9056
No log	7.5556	136	0.8161	0.2683	0.8161	0.9034
No log	7.6667	138	0.8006	0.2683	0.8006	0.8948
No log	7.7778	140	0.7854	0.3077	0.7854	0.8863
No log	7.8889	142	0.7766	0.3077	0.7766	0.8813
No log	8.0	144	0.7626	0.2597	0.7626	0.8733
No log	8.1111	146	0.7593	0.2222	0.7593	0.8714
No log	8.2222	148	0.7691	0.3250	0.7691	0.8770
No log	8.3333	150	0.7804	0.1750	0.7804	0.8834
No log	8.4444	152	0.7928	0.1750	0.7928	0.8904
No log	8.5556	154	0.7977	0.1750	0.7977	0.8932
No log	8.6667	156	0.7964	0.2222	0.7964	0.8924
No log	8.7778	158	0.7940	0.2683	0.7940	0.8910
No log	8.8889	160	0.7874	0.2222	0.7874	0.8873
No log	9.0	162	0.7793	0.2222	0.7793	0.8828
No log	9.1111	164	0.7746	0.2222	0.7746	0.8801
No log	9.2222	166	0.7712	0.2222	0.7712	0.8782
No log	9.3333	168	0.7691	0.2222	0.7691	0.8770
No log	9.4444	170	0.7677	0.2222	0.7677	0.8762
No log	9.5556	172	0.7661	0.2222	0.7661	0.8753
No log	9.6667	174	0.7620	0.2222	0.7620	0.8729
No log	9.7778	176	0.7602	0.2222	0.7602	0.8719
No log	9.8889	178	0.7585	0.2222	0.7585	0.8709
No log	10.0	180	0.7580	0.2222	0.7580	0.8707

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/Arabic_FineTuningAraBERT_AugV5_k1_task2_organization_fold1

Arabic_FineTuningAraBERT_AugV5_k1_task2_organization_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
Arabic_FineTuningAraBERT_AugV5_k1_task2_organization_fold1