Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.0952	2	5.3420	-0.0430	5.3420	2.3113
No log	0.1905	4	2.5573	0.1102	2.5573	1.5991
No log	0.2857	6	1.3043	0.1026	1.3043	1.1420
No log	0.3810	8	0.9925	0.0714	0.9925	0.9962
No log	0.4762	10	0.7182	0.1840	0.7182	0.8474
No log	0.5714	12	0.6658	0.3787	0.6658	0.8160
No log	0.6667	14	0.6866	0.5116	0.6866	0.8286
No log	0.7619	16	0.9924	0.3519	0.9924	0.9962
No log	0.8571	18	0.9394	0.3756	0.9394	0.9692
No log	0.9524	20	0.9815	0.3280	0.9815	0.9907
No log	1.0476	22	0.8543	0.4262	0.8543	0.9243
No log	1.1429	24	0.5238	0.5281	0.5238	0.7238
No log	1.2381	26	0.6482	0.3253	0.6482	0.8051
No log	1.3333	28	0.6687	0.2699	0.6687	0.8177
No log	1.4286	30	0.5113	0.4615	0.5113	0.7150
No log	1.5238	32	0.6465	0.4385	0.6465	0.8041
No log	1.6190	34	0.7745	0.3750	0.7745	0.8801
No log	1.7143	36	0.8349	0.4262	0.8349	0.9137
No log	1.8095	38	0.6139	0.4251	0.6139	0.7835
No log	1.9048	40	0.4707	0.5746	0.4707	0.6861
No log	2.0	42	0.4853	0.6169	0.4853	0.6967
No log	2.0952	44	0.5050	0.7492	0.5050	0.7107
No log	2.1905	46	0.5120	0.8069	0.5120	0.7155
No log	2.2857	48	0.5532	0.7508	0.5532	0.7437
No log	2.3810	50	0.5941	0.6994	0.5941	0.7707
No log	2.4762	52	0.6337	0.7571	0.6337	0.7961
No log	2.5714	54	0.7065	0.6465	0.7065	0.8405
No log	2.6667	56	0.6178	0.7667	0.6178	0.7860
No log	2.7619	58	0.5226	0.7508	0.5226	0.7229
No log	2.8571	60	0.4625	0.7758	0.4625	0.6801
No log	2.9524	62	0.4198	0.7805	0.4198	0.6479
No log	3.0476	64	0.5109	0.7220	0.5109	0.7147
No log	3.1429	66	0.4286	0.8048	0.4286	0.6546
No log	3.2381	68	0.4255	0.7586	0.4255	0.6523
No log	3.3333	70	0.4993	0.7279	0.4993	0.7066
No log	3.4286	72	0.5386	0.7279	0.5386	0.7339
No log	3.5238	74	0.5312	0.7667	0.5312	0.7288
No log	3.6190	76	0.5418	0.7667	0.5418	0.7361
No log	3.7143	78	0.5239	0.7667	0.5239	0.7238
No log	3.8095	80	0.5726	0.7667	0.5726	0.7567
No log	3.9048	82	0.5667	0.7667	0.5667	0.7528
No log	4.0	84	0.5289	0.7667	0.5289	0.7272
No log	4.0952	86	0.4228	0.7571	0.4228	0.6502
No log	4.1905	88	0.3870	0.8158	0.3870	0.6221
No log	4.2857	90	0.4624	0.7083	0.4624	0.6800
No log	4.3810	92	0.4199	0.8158	0.4199	0.6480
No log	4.4762	94	0.4471	0.7571	0.4471	0.6687
No log	4.5714	96	0.5580	0.7143	0.5580	0.7470
No log	4.6667	98	0.6161	0.6423	0.6161	0.7849
No log	4.7619	100	0.5935	0.6008	0.5935	0.7704
No log	4.8571	102	0.5267	0.7279	0.5267	0.7258
No log	4.9524	104	0.4740	0.7571	0.4740	0.6885
No log	5.0476	106	0.4464	0.7961	0.4464	0.6681
No log	5.1429	108	0.4571	0.7712	0.4571	0.6761
No log	5.2381	110	0.4946	0.7667	0.4946	0.7032
No log	5.3333	112	0.5897	0.7619	0.5897	0.7679
No log	5.4286	114	0.5717	0.7619	0.5717	0.7561
No log	5.5238	116	0.5526	0.7475	0.5526	0.7434
No log	5.6190	118	0.4179	0.8013	0.4179	0.6465
No log	5.7143	120	0.3136	0.7961	0.3136	0.5600
No log	5.8095	122	0.2988	0.8511	0.2988	0.5466
No log	5.9048	124	0.2763	0.8121	0.2763	0.5256
No log	6.0	126	0.3379	0.825	0.3379	0.5813
No log	6.0952	128	0.4985	0.7826	0.4985	0.7060
No log	6.1905	130	0.5650	0.7475	0.5650	0.7517
No log	6.2857	132	0.5457	0.7475	0.5457	0.7387
No log	6.3810	134	0.4350	0.7974	0.4350	0.6595
No log	6.4762	136	0.3297	0.8121	0.3297	0.5742
No log	6.5714	138	0.3289	0.8478	0.3289	0.5735
No log	6.6667	140	0.3382	0.8478	0.3382	0.5816
No log	6.7619	142	0.3470	0.7758	0.3470	0.5891
No log	6.8571	144	0.4470	0.7279	0.4470	0.6686
No log	6.9524	146	0.6598	0.6488	0.6598	0.8123
No log	7.0476	148	0.7816	0.5772	0.7816	0.8841
No log	7.1429	150	0.7909	0.5772	0.7909	0.8893
No log	7.2381	152	0.7420	0.6580	0.7420	0.8614
No log	7.3333	154	0.6296	0.7220	0.6296	0.7935
No log	7.4286	156	0.4822	0.7279	0.4822	0.6944
No log	7.5238	158	0.3867	0.7426	0.3867	0.6218
No log	7.6190	160	0.3621	0.7758	0.3621	0.6017
No log	7.7143	162	0.3648	0.7758	0.3648	0.6040
No log	7.8095	164	0.3807	0.7482	0.3807	0.6170
No log	7.9048	166	0.4301	0.7279	0.4301	0.6558
No log	8.0	168	0.5168	0.7273	0.5168	0.7189
No log	8.0952	170	0.5708	0.6873	0.5708	0.7555
No log	8.1905	172	0.5960	0.7219	0.5960	0.7720
No log	8.2857	174	0.5890	0.7219	0.5890	0.7675
No log	8.3810	176	0.5439	0.7219	0.5439	0.7375
No log	8.4762	178	0.4684	0.7279	0.4684	0.6844
No log	8.5714	180	0.3916	0.72	0.3916	0.6258
No log	8.6667	182	0.3595	0.7336	0.3595	0.5996
No log	8.7619	184	0.3639	0.7336	0.3639	0.6032
No log	8.8571	186	0.3867	0.7336	0.3867	0.6219
No log	8.9524	188	0.4263	0.72	0.4263	0.6529
No log	9.0476	190	0.4570	0.7279	0.4570	0.6760
No log	9.1429	192	0.4805	0.7273	0.4805	0.6932
No log	9.2381	194	0.5012	0.7273	0.5012	0.7080
No log	9.3333	196	0.5050	0.7273	0.5050	0.7107
No log	9.4286	198	0.4951	0.7279	0.4951	0.7037
No log	9.5238	200	0.4756	0.7279	0.4756	0.6896
No log	9.6190	202	0.4589	0.7279	0.4589	0.6775
No log	9.7143	204	0.4446	0.7279	0.4446	0.6667
No log	9.8095	206	0.4382	0.7279	0.4382	0.6620
No log	9.9048	208	0.4356	0.7279	0.4356	0.6600
No log	10.0	210	0.4354	0.7279	0.4354	0.6598

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/Arabic_FineTuningAraBERT_run3_AugV5_k1_task1_organization_fold1

Arabic_FineTuningAraBERT_run3_AugV5_k1_task1_organization_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
Arabic_FineTuningAraBERT_run3_AugV5_k1_task1_organization_fold1