Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1111	2	1.7928	0.1292	1.7928	1.3390
No log	0.2222	4	0.9583	0.2123	0.9583	0.9789
No log	0.3333	6	0.7879	0.2578	0.7879	0.8876
No log	0.4444	8	0.9472	0.2578	0.9472	0.9732
No log	0.5556	10	1.0086	0.2578	1.0086	1.0043
No log	0.6667	12	0.9672	0.4788	0.9672	0.9835
No log	0.7778	14	0.8457	0.4788	0.8457	0.9196
No log	0.8889	16	0.7678	0.4495	0.7678	0.8762
No log	1.0	18	0.6829	0.4495	0.6829	0.8264
No log	1.1111	20	0.6365	0.5467	0.6365	0.7978
No log	1.2222	22	0.6216	0.5143	0.6216	0.7884
No log	1.3333	24	0.6274	0.5143	0.6274	0.7921
No log	1.4444	26	0.6375	0.5467	0.6375	0.7984
No log	1.5556	28	0.6781	0.6486	0.6781	0.8235
No log	1.6667	30	0.7103	0.6486	0.7103	0.8428
No log	1.7778	32	0.7082	0.6486	0.7082	0.8416
No log	1.8889	34	0.6575	0.6341	0.6575	0.8109
No log	2.0	36	0.5872	0.6491	0.5872	0.7663
No log	2.1111	38	0.5495	0.6543	0.5495	0.7413
No log	2.2222	40	0.5489	0.6783	0.5489	0.7409
No log	2.3333	42	0.5998	0.6667	0.5998	0.7745
No log	2.4444	44	0.7486	0.6411	0.7486	0.8652
No log	2.5556	46	0.9372	0.5862	0.9372	0.9681
No log	2.6667	48	1.0378	0.5501	1.0378	1.0187
No log	2.7778	50	0.7891	0.5455	0.7891	0.8883
No log	2.8889	52	0.5723	0.5225	0.5723	0.7565
No log	3.0	54	0.5911	0.6439	0.5911	0.7688
No log	3.1111	56	0.5623	0.6037	0.5623	0.7499
No log	3.2222	58	0.5894	0.5866	0.5894	0.7677
No log	3.3333	60	0.7869	0.6411	0.7869	0.8871
No log	3.4444	62	1.0428	0.5796	1.0428	1.0212
No log	3.5556	64	1.0528	0.5796	1.0528	1.0261
No log	3.6667	66	0.9704	0.5796	0.9704	0.9851
No log	3.7778	68	0.8244	0.5796	0.8244	0.9080
No log	3.8889	70	0.6454	0.6675	0.6454	0.8033
No log	4.0	72	0.5063	0.6438	0.5063	0.7115
No log	4.1111	74	0.4446	0.7403	0.4446	0.6668
No log	4.2222	76	0.4184	0.7403	0.4184	0.6468
No log	4.3333	78	0.4295	0.7403	0.4295	0.6554
No log	4.4444	80	0.4808	0.7136	0.4808	0.6934
No log	4.5556	82	0.5650	0.7136	0.5650	0.7517
No log	4.6667	84	0.6734	0.6462	0.6734	0.8206
No log	4.7778	86	0.6902	0.6462	0.6902	0.8308
No log	4.8889	88	0.6228	0.6909	0.6228	0.7892
No log	5.0	90	0.5495	0.7059	0.5495	0.7413
No log	5.1111	92	0.5096	0.7176	0.5096	0.7138
No log	5.2222	94	0.4790	0.7176	0.4790	0.6921
No log	5.3333	96	0.4419	0.7176	0.4419	0.6647
No log	5.4444	98	0.4478	0.7264	0.4478	0.6692
No log	5.5556	100	0.5006	0.7267	0.5006	0.7076
No log	5.6667	102	0.5499	0.6909	0.5499	0.7415
No log	5.7778	104	0.6029	0.6909	0.6029	0.7765
No log	5.8889	106	0.5949	0.6909	0.5949	0.7713
No log	6.0	108	0.5523	0.7018	0.5523	0.7431
No log	6.1111	110	0.5786	0.7347	0.5786	0.7606
No log	6.2222	112	0.6186	0.7347	0.6186	0.7865
No log	6.3333	114	0.7293	0.7412	0.7293	0.8540
No log	6.4444	116	0.8882	0.6604	0.8882	0.9424
No log	6.5556	118	1.1051	0.5968	1.1051	1.0512
No log	6.6667	120	1.1479	0.5540	1.1479	1.0714
No log	6.7778	122	1.0343	0.6154	1.0343	1.0170
No log	6.8889	124	0.8234	0.6586	0.8234	0.9074
No log	7.0	126	0.6522	0.7002	0.6522	0.8076
No log	7.1111	128	0.5384	0.7463	0.5384	0.7337
No log	7.2222	130	0.5072	0.7463	0.5072	0.7122
No log	7.3333	132	0.5252	0.7463	0.5252	0.7247
No log	7.4444	134	0.6259	0.7137	0.6259	0.7911
No log	7.5556	136	0.6987	0.7009	0.6987	0.8359
No log	7.6667	138	0.7612	0.7028	0.7612	0.8725
No log	7.7778	140	0.7857	0.7217	0.7857	0.8864
No log	7.8889	142	0.7482	0.7217	0.7482	0.8650
No log	8.0	144	0.6871	0.7405	0.6871	0.8289
No log	8.1111	146	0.6513	0.7343	0.6513	0.8070
No log	8.2222	148	0.6402	0.7343	0.6402	0.8001
No log	8.3333	150	0.6467	0.7343	0.6467	0.8042
No log	8.4444	152	0.6395	0.7343	0.6395	0.7997
No log	8.5556	154	0.6161	0.7343	0.6161	0.7849
No log	8.6667	156	0.5626	0.7347	0.5626	0.7501
No log	8.7778	158	0.5206	0.7463	0.5206	0.7215
No log	8.8889	160	0.5083	0.7463	0.5083	0.7129
No log	9.0	162	0.5037	0.7463	0.5037	0.7098
No log	9.1111	164	0.5024	0.7463	0.5024	0.7088
No log	9.2222	166	0.5019	0.7463	0.5019	0.7085
No log	9.3333	168	0.5094	0.7451	0.5094	0.7137
No log	9.4444	170	0.5277	0.7451	0.5277	0.7264
No log	9.5556	172	0.5487	0.7451	0.5487	0.7407
No log	9.6667	174	0.5736	0.7343	0.5736	0.7573
No log	9.7778	176	0.5899	0.7343	0.5899	0.7681
No log	9.8889	178	0.5972	0.7343	0.5972	0.7728
No log	10.0	180	0.5985	0.7343	0.5985	0.7736

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/Arabic_FineTuningAraBERT_AugV0_k3_task5_organization_fold0

Arabic_FineTuningAraBERT_AugV0_k3_task5_organization_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
Arabic_FineTuningAraBERT_AugV0_k3_task5_organization_fold0