Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1111	2	5.0118	-0.0587	5.0118	2.2387
No log	0.2222	4	2.5358	-0.0229	2.5358	1.5924
No log	0.3333	6	0.9975	0.1437	0.9975	0.9987
No log	0.4444	8	0.6424	0.4857	0.6424	0.8015
No log	0.5556	10	0.5580	0.2373	0.5580	0.7470
No log	0.6667	12	0.6387	0.2186	0.6387	0.7992
No log	0.7778	14	0.5632	0.2759	0.5632	0.7505
No log	0.8889	16	0.8775	0.3046	0.8775	0.9367
No log	1.0	18	1.4768	0.2309	1.4768	1.2152
No log	1.1111	20	1.4519	0.2775	1.4519	1.2050
No log	1.2222	22	0.9542	0.2527	0.9542	0.9768
No log	1.3333	24	0.7827	0.3581	0.7827	0.8847
No log	1.4444	26	0.7802	0.1923	0.7802	0.8833
No log	1.5556	28	0.8365	0.1923	0.8365	0.9146
No log	1.6667	30	0.7247	0.3197	0.7247	0.8513
No log	1.7778	32	0.6360	0.1560	0.6360	0.7975
No log	1.8889	34	0.6313	0.2373	0.6313	0.7946
No log	2.0	36	0.6584	0.3467	0.6584	0.8114
No log	2.1111	38	0.6744	0.3467	0.6744	0.8212
No log	2.2222	40	0.6889	0.2921	0.6889	0.8300
No log	2.3333	42	0.7217	0.2759	0.7217	0.8495
No log	2.4444	44	0.6585	0.2921	0.6585	0.8115
No log	2.5556	46	0.5960	0.2696	0.5960	0.7720
No log	2.6667	48	0.6685	0.4375	0.6685	0.8176
No log	2.7778	50	0.6964	0.3046	0.6964	0.8345
No log	2.8889	52	0.6323	0.4375	0.6323	0.7952
No log	3.0	54	0.6324	0.3046	0.6324	0.7952
No log	3.1111	56	0.6850	0.2664	0.6850	0.8277
No log	3.2222	58	0.6698	0.2664	0.6698	0.8184
No log	3.3333	60	0.6382	0.2889	0.6382	0.7989
No log	3.4444	62	0.6290	0.1755	0.6290	0.7931
No log	3.5556	64	0.6198	0.1560	0.6198	0.7873
No log	3.6667	66	0.6448	0.2154	0.6448	0.8030
No log	3.7778	68	0.6320	0.3171	0.6320	0.7950
No log	3.8889	70	0.5889	0.3226	0.5889	0.7674
No log	4.0	72	0.5879	0.3226	0.5879	0.7668
No log	4.1111	74	0.5861	0.3226	0.5861	0.7656
No log	4.2222	76	0.5900	0.3226	0.5900	0.7681
No log	4.3333	78	0.5910	0.3307	0.5910	0.7687
No log	4.4444	80	0.6630	0.475	0.6630	0.8143
No log	4.5556	82	0.7283	0.4378	0.7283	0.8534
No log	4.6667	84	0.7064	0.475	0.7064	0.8405
No log	4.7778	86	0.6501	0.5164	0.6501	0.8063
No log	4.8889	88	0.6589	0.5473	0.6589	0.8117
No log	5.0	90	0.7139	0.475	0.7139	0.8449
No log	5.1111	92	0.6910	0.4483	0.6910	0.8313
No log	5.2222	94	0.6191	0.4270	0.6191	0.7868
No log	5.3333	96	0.6079	0.4368	0.6079	0.7797
No log	5.4444	98	0.6160	0.4670	0.6160	0.7849
No log	5.5556	100	0.6328	0.3708	0.6328	0.7955
No log	5.6667	102	0.6621	0.3708	0.6621	0.8137
No log	5.7778	104	0.6737	0.3251	0.6737	0.8208
No log	5.8889	106	0.6230	0.4483	0.6230	0.7893
No log	6.0	108	0.5879	0.5067	0.5879	0.7668
No log	6.1111	110	0.5995	0.5116	0.5995	0.7743
No log	6.2222	112	0.5855	0.5116	0.5855	0.7652
No log	6.3333	114	0.6016	0.4483	0.6016	0.7757
No log	6.4444	116	0.6661	0.5164	0.6661	0.8161
No log	6.5556	118	0.6856	0.5164	0.6856	0.8280
No log	6.6667	120	0.6506	0.5191	0.6506	0.8066
No log	6.7778	122	0.6585	0.5477	0.6585	0.8115
No log	6.8889	124	0.6852	0.5473	0.6852	0.8278
No log	7.0	126	0.6736	0.5473	0.6736	0.8207
No log	7.1111	128	0.6588	0.5477	0.6588	0.8117
No log	7.2222	130	0.6591	0.5473	0.6591	0.8118
No log	7.3333	132	0.6075	0.4563	0.6075	0.7794
No log	7.4444	134	0.5766	0.3981	0.5766	0.7593
No log	7.5556	136	0.5879	0.5067	0.5879	0.7668
No log	7.6667	138	0.5825	0.5067	0.5825	0.7632
No log	7.7778	140	0.5807	0.3981	0.5807	0.7620
No log	7.8889	142	0.6283	0.5191	0.6283	0.7927
No log	8.0	144	0.7031	0.5396	0.7031	0.8385
No log	8.1111	146	0.7288	0.4667	0.7288	0.8537
No log	8.2222	148	0.7254	0.5396	0.7254	0.8517
No log	8.3333	150	0.7050	0.5396	0.7050	0.8396
No log	8.4444	152	0.6496	0.4831	0.6496	0.8060
No log	8.5556	154	0.6082	0.4270	0.6082	0.7799
No log	8.6667	156	0.6007	0.4270	0.6007	0.7751
No log	8.7778	158	0.5980	0.4270	0.5980	0.7733
No log	8.8889	160	0.5953	0.3981	0.5953	0.7715
No log	9.0	162	0.5984	0.3981	0.5984	0.7735
No log	9.1111	164	0.6023	0.3981	0.6023	0.7761
No log	9.2222	166	0.6033	0.3981	0.6033	0.7767
No log	9.3333	168	0.6083	0.4270	0.6083	0.7799
No log	9.4444	170	0.6142	0.4270	0.6142	0.7837
No log	9.5556	172	0.6195	0.4270	0.6195	0.7871
No log	9.6667	174	0.6240	0.4270	0.6240	0.7899
No log	9.7778	176	0.6275	0.4563	0.6275	0.7922
No log	9.8889	178	0.6322	0.5191	0.6322	0.7951
No log	10.0	180	0.6349	0.4831	0.6349	0.7968

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_fold0

Arabic_FineTuningAraBERT_AugV5_k1_task2_organization_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
Arabic_FineTuningAraBERT_AugV5_k1_task2_organization_fold0