Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1818	2	3.3310	-0.0114	3.3310	1.8251
No log	0.3636	4	1.5631	-0.0070	1.5631	1.2503
No log	0.5455	6	1.7101	0.0296	1.7101	1.3077
No log	0.7273	8	1.4707	0.0728	1.4707	1.2127
No log	0.9091	10	0.5818	0.1773	0.5818	0.7628
No log	1.0909	12	0.6154	0.0569	0.6154	0.7845
No log	1.2727	14	0.5696	0.0569	0.5696	0.7547
No log	1.4545	16	0.6529	0.1746	0.6529	0.8080
No log	1.6364	18	1.0771	0.0476	1.0771	1.0378
No log	1.8182	20	0.9195	0.0894	0.9195	0.9589
No log	2.0	22	0.6536	0.1746	0.6536	0.8084
No log	2.1818	24	0.5611	0.2000	0.5611	0.7491
No log	2.3636	26	0.6499	0.0952	0.6499	0.8062
No log	2.5455	28	0.7039	0.1675	0.7039	0.8390
No log	2.7273	30	0.5467	0.2222	0.5467	0.7394
No log	2.9091	32	0.5690	0.1145	0.5690	0.7543
No log	3.0909	34	0.5834	0.0949	0.5834	0.7638
No log	3.2727	36	0.6942	0.1568	0.6942	0.8332
No log	3.4545	38	0.7973	0.1683	0.7973	0.8929
No log	3.6364	40	0.7816	0.1579	0.7816	0.8841
No log	3.8182	42	0.8055	0.0870	0.8055	0.8975
No log	4.0	44	0.8504	0.0711	0.8504	0.9222
No log	4.1818	46	0.9149	0.1055	0.9149	0.9565
No log	4.3636	48	1.0278	0.0968	1.0278	1.0138
No log	4.5455	50	1.0419	0.0672	1.0419	1.0207
No log	4.7273	52	0.9516	0.1635	0.9516	0.9755
No log	4.9091	54	0.9566	0.2253	0.9566	0.9780
No log	5.0909	56	1.0181	0.1439	1.0181	1.0090
No log	5.2727	58	1.1269	0.1062	1.1269	1.0616
No log	5.4545	60	1.0487	0.1557	1.0487	1.0241
No log	5.6364	62	1.0241	0.1498	1.0241	1.0120
No log	5.8182	64	1.0584	0.1278	1.0584	1.0288
No log	6.0	66	1.1549	0.1220	1.1549	1.0747
No log	6.1818	68	1.1748	0.1241	1.1748	1.0839
No log	6.3636	70	1.1018	0.1254	1.1018	1.0497
No log	6.5455	72	0.9969	0.1292	0.9969	0.9985
No log	6.7273	74	0.9067	0.1799	0.9067	0.9522
No log	6.9091	76	0.8929	0.2134	0.8929	0.9449
No log	7.0909	78	0.9280	0.1807	0.9280	0.9633
No log	7.2727	80	1.0341	0.1145	1.0341	1.0169
No log	7.4545	82	1.0820	0.1533	1.0820	1.0402
No log	7.6364	84	1.0313	0.1145	1.0313	1.0155
No log	7.8182	86	1.0008	0.1094	1.0008	1.0004
No log	8.0	88	0.9168	0.1875	0.9168	0.9575
No log	8.1818	90	0.8823	0.2263	0.8823	0.9393
No log	8.3636	92	0.8762	0.1795	0.8762	0.9360
No log	8.5455	94	0.8998	0.1464	0.8998	0.9486
No log	8.7273	96	0.9399	0.2581	0.9399	0.9695
No log	8.9091	98	0.9872	0.1811	0.9872	0.9936
No log	9.0909	100	1.0391	0.0977	1.0391	1.0194
No log	9.2727	102	1.0871	0.0815	1.0871	1.0426
No log	9.4545	104	1.1207	0.0882	1.1207	1.0586
No log	9.6364	106	1.1352	0.1191	1.1352	1.0655
No log	9.8182	108	1.1333	0.0903	1.1333	1.0646
No log	10.0	110	1.1306	0.0903	1.1306	1.0633

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/ArabicNewSplits4_FineTuningAraBERT_run1_AugV5_k2_task3_organization

ArabicNewSplits4_FineTuningAraBERT_run1_AugV5_k2_task3_organization

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
ArabicNewSplits4_FineTuningAraBERT_run1_AugV5_k2_task3_organization