Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.2222	2	3.8978	0.0114	3.8978	1.9743
No log	0.4444	4	2.6706	0.0063	2.6706	1.6342
No log	0.6667	6	1.7795	0.0528	1.7795	1.3340
No log	0.8889	8	1.1347	0.0	1.1347	1.0652
No log	1.1111	10	0.8463	0.0	0.8463	0.9199
No log	1.3333	12	0.8256	0.0378	0.8256	0.9086
No log	1.5556	14	0.7445	-0.1618	0.7445	0.8628
No log	1.7778	16	0.7344	0.0481	0.7344	0.8570
No log	2.0	18	0.7526	-0.0734	0.7526	0.8675
No log	2.2222	20	0.7531	-0.0946	0.7531	0.8678
No log	2.4444	22	0.7999	0.0378	0.7999	0.8944
No log	2.6667	24	0.8108	0.0378	0.8108	0.9005
No log	2.8889	26	0.8201	0.0378	0.8201	0.9056
No log	3.1111	28	0.7884	0.0378	0.7884	0.8879
No log	3.3333	30	0.7985	0.0378	0.7985	0.8936
No log	3.5556	32	0.7757	0.0378	0.7757	0.8808
No log	3.7778	34	0.7784	0.0187	0.7784	0.8823
No log	4.0	36	0.7551	0.0378	0.7551	0.8689
No log	4.2222	38	0.7386	0.0849	0.7386	0.8594
No log	4.4444	40	0.7461	-0.0332	0.7461	0.8638
No log	4.6667	42	0.7539	-0.0530	0.7539	0.8683
No log	4.8889	44	0.7401	0.0986	0.7401	0.8603
No log	5.1111	46	0.7204	0.0226	0.7204	0.8488
No log	5.3333	48	0.7156	0.0	0.7156	0.8460
No log	5.5556	50	0.7136	0.0	0.7136	0.8448
No log	5.7778	52	0.7128	0.0	0.7128	0.8443
No log	6.0	54	0.7170	0.0226	0.7170	0.8468
No log	6.2222	56	0.7558	-0.0938	0.7558	0.8693
No log	6.4444	58	0.8488	0.0187	0.8488	0.9213
No log	6.6667	60	0.8420	0.0378	0.8420	0.9176
No log	6.8889	62	0.8054	-0.1513	0.8054	0.8974
No log	7.1111	64	0.7708	-0.0930	0.7708	0.8779
No log	7.3333	66	0.7335	0.0569	0.7335	0.8564
No log	7.5556	68	0.7178	-0.0022	0.7178	0.8472
No log	7.7778	70	0.7149	-0.0022	0.7149	0.8455
No log	8.0	72	0.7148	-0.0022	0.7148	0.8454
No log	8.2222	74	0.7162	-0.0022	0.7162	0.8463
No log	8.4444	76	0.7173	-0.0022	0.7173	0.8469
No log	8.6667	78	0.7195	-0.0022	0.7195	0.8482
No log	8.8889	80	0.7280	0.1777	0.7280	0.8532
No log	9.1111	82	0.7420	0.0569	0.7420	0.8614
No log	9.3333	84	0.7550	0.0569	0.7550	0.8689
No log	9.5556	86	0.7637	0.0120	0.7637	0.8739
No log	9.7778	88	0.7652	0.0120	0.7652	0.8748
No log	10.0	90	0.7650	0.0120	0.7650	0.8746

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/ArabicNewSplits_FineTuningAraBERT_AugV5_k4_task3_organization_fold1

ArabicNewSplits_FineTuningAraBERT_AugV5_k4_task3_organization_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
ArabicNewSplits_FineTuningAraBERT_AugV5_k4_task3_organization_fold1