Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1176	2	4.3515	0.0	4.3515	2.0860
No log	0.2353	4	3.0124	0.0785	3.0124	1.7356
No log	0.3529	6	1.0535	0.2029	1.0535	1.0264
No log	0.4706	8	0.9971	0.0320	0.9971	0.9985
No log	0.5882	10	0.9710	0.0320	0.9710	0.9854
No log	0.7059	12	0.8794	0.0	0.8794	0.9378
No log	0.8235	14	0.7962	0.0	0.7962	0.8923
No log	0.9412	16	0.7389	0.0	0.7389	0.8596
No log	1.0588	18	0.8726	0.2143	0.8726	0.9341
No log	1.1765	20	0.9741	0.1987	0.9741	0.9869
No log	1.2941	22	1.0205	0.1987	1.0205	1.0102
No log	1.4118	24	0.8038	0.0	0.8038	0.8966
No log	1.5294	26	0.6910	0.0	0.6910	0.8313
No log	1.6471	28	0.7162	0.0	0.7162	0.8463
No log	1.7647	30	0.7492	0.0	0.7492	0.8655
No log	1.8824	32	0.7341	0.0	0.7341	0.8568
No log	2.0	34	0.7486	0.0	0.7486	0.8652
No log	2.1176	36	0.7591	0.0	0.7591	0.8712
No log	2.2353	38	0.7643	0.0	0.7643	0.8743
No log	2.3529	40	0.8451	0.0	0.8451	0.9193
No log	2.4706	42	0.8951	0.0179	0.8951	0.9461
No log	2.5882	44	0.8647	0.0179	0.8647	0.9299
No log	2.7059	46	0.9410	0.3623	0.9410	0.9701
No log	2.8235	48	0.8734	0.2080	0.8734	0.9346
No log	2.9412	50	0.7426	0.0	0.7426	0.8617
No log	3.0588	52	0.7088	0.0	0.7088	0.8419
No log	3.1765	54	0.7989	0.0	0.7989	0.8938
No log	3.2941	56	0.7753	0.0	0.7753	0.8805
No log	3.4118	58	0.7551	0.0	0.7551	0.8690
No log	3.5294	60	0.8007	0.0179	0.8007	0.8948
No log	3.6471	62	0.7722	0.0	0.7722	0.8788
No log	3.7647	64	0.7240	0.0	0.7240	0.8509
No log	3.8824	66	0.7512	0.0	0.7512	0.8667
No log	4.0	68	0.7342	0.0	0.7342	0.8568
No log	4.1176	70	0.7459	0.0	0.7459	0.8637
No log	4.2353	72	0.7317	0.0	0.7317	0.8554
No log	4.3529	74	0.7078	0.0	0.7078	0.8413
No log	4.4706	76	0.7194	0.0	0.7194	0.8482
No log	4.5882	78	0.7849	-0.0342	0.7849	0.8860
No log	4.7059	80	0.7504	0.0	0.7504	0.8662
No log	4.8235	82	0.7471	0.0	0.7471	0.8643
No log	4.9412	84	0.7720	0.0	0.7720	0.8786
No log	5.0588	86	0.8094	0.0	0.8094	0.8997
No log	5.1765	88	0.8448	-0.0185	0.8448	0.9191
No log	5.2941	90	0.8859	-0.0185	0.8859	0.9412
No log	5.4118	92	0.8876	-0.0185	0.8876	0.9421
No log	5.5294	94	0.8897	0.0320	0.8897	0.9432
No log	5.6471	96	0.9142	0.0435	0.9142	0.9562
No log	5.7647	98	0.9020	0.0435	0.9020	0.9498
No log	5.8824	100	0.8796	-0.1786	0.8796	0.9379
No log	6.0	102	0.8797	0.0320	0.8797	0.9379
No log	6.1176	104	0.8725	0.0320	0.8725	0.9341
No log	6.2353	106	0.8987	0.0320	0.8987	0.9480
No log	6.3529	108	0.8889	0.0320	0.8889	0.9428
No log	6.4706	110	0.8939	0.0320	0.8939	0.9455
No log	6.5882	112	0.8681	0.0320	0.8681	0.9317
No log	6.7059	114	0.8713	0.0320	0.8713	0.9334
No log	6.8235	116	0.8688	0.0149	0.8688	0.9321
No log	6.9412	118	0.8986	-0.1818	0.8986	0.9479
No log	7.0588	120	0.8865	-0.1818	0.8865	0.9415
No log	7.1765	122	0.8682	0.0149	0.8682	0.9318
No log	7.2941	124	0.8765	0.0149	0.8765	0.9362
No log	7.4118	126	0.8902	0.0149	0.8902	0.9435
No log	7.5294	128	0.9038	0.0149	0.9038	0.9507
No log	7.6471	130	0.8986	0.0149	0.8986	0.9480
No log	7.7647	132	0.9039	0.0149	0.9039	0.9507
No log	7.8824	134	0.8929	0.0149	0.8929	0.9449
No log	8.0	136	0.8875	0.0149	0.8875	0.9421
No log	8.1176	138	0.8870	0.0149	0.8870	0.9418
No log	8.2353	140	0.8945	0.0149	0.8945	0.9458
No log	8.3529	142	0.8958	0.0149	0.8958	0.9465
No log	8.4706	144	0.8975	0.0149	0.8975	0.9474
No log	8.5882	146	0.8993	0.0149	0.8993	0.9483
No log	8.7059	148	0.9085	0.0320	0.9085	0.9532
No log	8.8235	150	0.9137	0.0320	0.9137	0.9559
No log	8.9412	152	0.9113	0.0320	0.9113	0.9546
No log	9.0588	154	0.9073	0.0149	0.9073	0.9525
No log	9.1765	156	0.9079	0.0149	0.9079	0.9528
No log	9.2941	158	0.9108	0.0149	0.9108	0.9544
No log	9.4118	160	0.9123	0.0149	0.9123	0.9552
No log	9.5294	162	0.9071	0.0149	0.9071	0.9524
No log	9.6471	164	0.9020	0.0149	0.9020	0.9497
No log	9.7647	166	0.9004	0.0149	0.9004	0.9489
No log	9.8824	168	0.8999	0.0320	0.8999	0.9486
No log	10.0	170	0.8997	0.0320	0.8997	0.9485

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/Arabic_FineTuningAraBERT_AugV0_k4_task3_organization_fold0

Arabic_FineTuningAraBERT_AugV0_k4_task3_organization_fold0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
Arabic_FineTuningAraBERT_AugV0_k4_task3_organization_fold0