Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.0909	2	3.3780	-0.0053	3.3780	1.8379
No log	0.1818	4	1.6305	-0.0070	1.6305	1.2769
No log	0.2727	6	1.3916	0.0255	1.3916	1.1797
No log	0.3636	8	0.9833	-0.0081	0.9833	0.9916
No log	0.4545	10	0.7466	-0.0370	0.7466	0.8640
No log	0.5455	12	0.6741	-0.0794	0.6741	0.8210
No log	0.6364	14	0.5988	0.0	0.5988	0.7738
No log	0.7273	16	0.6051	0.0	0.6051	0.7779
No log	0.8182	18	0.5987	0.0	0.5987	0.7737
No log	0.9091	20	0.6543	0.0815	0.6543	0.8089
No log	1.0	22	0.7785	0.1392	0.7785	0.8823
No log	1.0909	24	0.8146	0.2000	0.8146	0.9026
No log	1.1818	26	0.6702	0.3333	0.6702	0.8187
No log	1.2727	28	0.5790	0.0222	0.5790	0.7609
No log	1.3636	30	0.6090	0.0	0.6090	0.7804
No log	1.4545	32	0.5934	0.1206	0.5934	0.7703
No log	1.5455	34	0.9757	0.0667	0.9757	0.9878
No log	1.6364	36	1.0799	0.0843	1.0799	1.0392
No log	1.7273	38	0.6603	0.1828	0.6603	0.8126
No log	1.8182	40	0.5970	0.1895	0.5970	0.7727
No log	1.9091	42	0.6101	0.1515	0.6101	0.7811
No log	2.0	44	0.7627	0.2762	0.7627	0.8733
No log	2.0909	46	1.0428	0.1276	1.0428	1.0212
No log	2.1818	48	1.1338	0.1730	1.1338	1.0648
No log	2.2727	50	0.8391	0.2762	0.8391	0.9160
No log	2.3636	52	0.6435	0.2281	0.6435	0.8022
No log	2.4545	54	0.6168	0.0476	0.6168	0.7854
No log	2.5455	56	0.6396	0.0388	0.6396	0.7997
No log	2.6364	58	0.6547	0.0388	0.6547	0.8092
No log	2.7273	60	0.6913	0.1724	0.6913	0.8315
No log	2.8182	62	0.7952	0.1795	0.7952	0.8917
No log	2.9091	64	0.8256	0.3242	0.8256	0.9086
No log	3.0	66	1.0090	0.264	1.0090	1.0045
No log	3.0909	68	1.2327	0.2248	1.2327	1.1103
No log	3.1818	70	1.1986	0.1940	1.1986	1.0948
No log	3.2727	72	0.8914	0.2811	0.8914	0.9442
No log	3.3636	74	0.7371	0.1746	0.7371	0.8586
No log	3.4545	76	0.7581	0.2077	0.7581	0.8707
No log	3.5455	78	0.7516	0.2381	0.7516	0.8670
No log	3.6364	80	0.6268	0.0455	0.6268	0.7917
No log	3.7273	82	0.5898	-0.0732	0.5898	0.7680
No log	3.8182	84	0.5959	0.0233	0.5959	0.7720
No log	3.9091	86	0.6857	0.2487	0.6857	0.8281
No log	4.0	88	0.7224	0.2453	0.7224	0.8500
No log	4.0909	90	0.6358	0.1915	0.6358	0.7974
No log	4.1818	92	0.6443	0.2332	0.6443	0.8027
No log	4.2727	94	0.6639	0.3171	0.6639	0.8148
No log	4.3636	96	0.8075	0.3600	0.8075	0.8986
No log	4.4545	98	0.7550	0.3821	0.7550	0.8689
No log	4.5455	100	0.6667	0.2961	0.6667	0.8165
No log	4.6364	102	0.6807	0.2653	0.6807	0.8250
No log	4.7273	104	0.7977	0.4504	0.7977	0.8931
No log	4.8182	106	0.7852	0.4016	0.7852	0.8861
No log	4.9091	108	0.6231	0.3548	0.6231	0.7894
No log	5.0	110	0.6949	0.3874	0.6949	0.8336
No log	5.0909	112	0.7180	0.4027	0.7180	0.8473
No log	5.1818	114	0.6557	0.3394	0.6557	0.8098
No log	5.2727	116	0.7822	0.3226	0.7822	0.8844
No log	5.3636	118	0.8001	0.3226	0.8001	0.8945
No log	5.4545	120	0.7630	0.3016	0.7630	0.8735
No log	5.5455	122	0.7004	0.3648	0.7004	0.8369
No log	5.6364	124	0.6889	0.3648	0.6889	0.8300
No log	5.7273	126	0.6873	0.3833	0.6873	0.8290
No log	5.8182	128	0.7260	0.3091	0.7260	0.8520
No log	5.9091	130	0.7161	0.3571	0.7161	0.8462
No log	6.0	132	0.8306	0.2727	0.8306	0.9114
No log	6.0909	134	1.0150	0.2990	1.0150	1.0075
No log	6.1818	136	0.8954	0.3460	0.8954	0.9463
No log	6.2727	138	0.7215	0.3648	0.7215	0.8494
No log	6.3636	140	0.7117	0.3427	0.7117	0.8436
No log	6.4545	142	0.7142	0.3973	0.7142	0.8451
No log	6.5455	144	0.6860	0.3208	0.6860	0.8283
No log	6.6364	146	0.6752	0.3180	0.6752	0.8217
No log	6.7273	148	0.7624	0.3306	0.7624	0.8732
No log	6.8182	150	0.7074	0.3021	0.7074	0.8411
No log	6.9091	152	0.6726	0.3080	0.6726	0.8201
No log	7.0	154	0.6431	0.3488	0.6431	0.8019
No log	7.0909	156	0.6401	0.3818	0.6401	0.8000
No log	7.1818	158	0.6264	0.3607	0.6264	0.7914
No log	7.2727	160	0.6705	0.3021	0.6705	0.8188
No log	7.3636	162	0.6396	0.3684	0.6396	0.7998
No log	7.4545	164	0.6256	0.4133	0.6256	0.7909
No log	7.5455	166	0.6570	0.4286	0.6570	0.8105
No log	7.6364	168	0.6627	0.4178	0.6627	0.8141
No log	7.7273	170	0.6529	0.3585	0.6529	0.8080
No log	7.8182	172	0.6597	0.3761	0.6597	0.8122
No log	7.9091	174	0.6614	0.3950	0.6614	0.8133
No log	8.0	176	0.6627	0.3898	0.6627	0.8141
No log	8.0909	178	0.6758	0.3898	0.6758	0.8220
No log	8.1818	180	0.6640	0.3898	0.6640	0.8149
No log	8.2727	182	0.6478	0.3833	0.6478	0.8049
No log	8.3636	184	0.6412	0.3488	0.6412	0.8007
No log	8.4545	186	0.6431	0.3786	0.6431	0.8019
No log	8.5455	188	0.6341	0.3684	0.6341	0.7963
No log	8.6364	190	0.6213	0.3803	0.6213	0.7882
No log	8.7273	192	0.6279	0.3874	0.6279	0.7924
No log	8.8182	194	0.6341	0.4133	0.6341	0.7963
No log	8.9091	196	0.6374	0.4035	0.6374	0.7984
No log	9.0	198	0.6273	0.3778	0.6273	0.7920
No log	9.0909	200	0.6300	0.3778	0.6300	0.7937
No log	9.1818	202	0.6251	0.3778	0.6251	0.7906
No log	9.2727	204	0.6242	0.3874	0.6242	0.7901
No log	9.3636	206	0.6291	0.3778	0.6291	0.7932
No log	9.4545	208	0.6327	0.3778	0.6327	0.7955
No log	9.5455	210	0.6314	0.3778	0.6314	0.7946
No log	9.6364	212	0.6304	0.3874	0.6304	0.7940
No log	9.7273	214	0.6274	0.3874	0.6274	0.7921
No log	9.8182	216	0.6249	0.3973	0.6249	0.7905
No log	9.9091	218	0.6239	0.4074	0.6239	0.7899
No log	10.0	220	0.6238	0.4074	0.6238	0.7898

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/ArabicNewSplits4_FineTuningAraBERT_run3_AugV5_k5_task3_organization

ArabicNewSplits4_FineTuningAraBERT_run3_AugV5_k5_task3_organization

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
ArabicNewSplits4_FineTuningAraBERT_run3_AugV5_k5_task3_organization