Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1538	2	4.8755	-0.0722	4.8755	2.2081
No log	0.3077	4	3.0731	0.0738	3.0731	1.7530
No log	0.4615	6	1.7811	0.1254	1.7811	1.3346
No log	0.6154	8	1.3472	0.1296	1.3472	1.1607
No log	0.7692	10	1.2827	0.0701	1.2827	1.1326
No log	0.9231	12	1.2158	0.0899	1.2158	1.1026
No log	1.0769	14	1.0297	0.3445	1.0297	1.0147
No log	1.2308	16	1.1103	0.2736	1.1103	1.0537
No log	1.3846	18	1.1941	0.1648	1.1941	1.0927
No log	1.5385	20	1.1982	0.2471	1.1982	1.0946
No log	1.6923	22	1.1769	0.3050	1.1769	1.0848
No log	1.8462	24	1.1307	0.3145	1.1307	1.0633
No log	2.0	26	1.1225	0.3198	1.1225	1.0595
No log	2.1538	28	1.2005	0.1301	1.2005	1.0957
No log	2.3077	30	1.2531	0.1503	1.2531	1.1194
No log	2.4615	32	1.1448	0.2230	1.1448	1.0700
No log	2.6154	34	1.0100	0.3793	1.0100	1.0050
No log	2.7692	36	0.9753	0.3571	0.9753	0.9876
No log	2.9231	38	0.9982	0.2771	0.9982	0.9991
No log	3.0769	40	0.9904	0.3423	0.9904	0.9952
No log	3.2308	42	1.0048	0.3717	1.0048	1.0024
No log	3.3846	44	1.0774	0.2528	1.0774	1.0380
No log	3.5385	46	1.3022	0.2826	1.3022	1.1411
No log	3.6923	48	1.4397	0.1888	1.4397	1.1999
No log	3.8462	50	1.2720	0.4219	1.2720	1.1278
No log	4.0	52	1.1023	0.2721	1.1023	1.0499
No log	4.1538	54	1.0140	0.5071	1.0140	1.0070
No log	4.3077	56	1.0495	0.4357	1.0495	1.0244
No log	4.4615	58	1.0388	0.4068	1.0388	1.0192
No log	4.6154	60	1.0341	0.4583	1.0341	1.0169
No log	4.7692	62	1.0435	0.4559	1.0435	1.0215
No log	4.9231	64	1.0465	0.4393	1.0465	1.0230
No log	5.0769	66	1.0186	0.5103	1.0186	1.0093
No log	5.2308	68	0.9823	0.5777	0.9823	0.9911
No log	5.3846	70	0.9632	0.5745	0.9632	0.9814
No log	5.5385	72	0.9583	0.5745	0.9583	0.9789
No log	5.6923	74	0.9579	0.5629	0.9579	0.9787
No log	5.8462	76	0.9809	0.5745	0.9809	0.9904
No log	6.0	78	1.0332	0.4669	1.0332	1.0165
No log	6.1538	80	1.0979	0.4391	1.0979	1.0478
No log	6.3077	82	1.1242	0.4253	1.1242	1.0603
No log	6.4615	84	1.0957	0.4391	1.0957	1.0468
No log	6.6154	86	1.0546	0.4945	1.0546	1.0270
No log	6.7692	88	1.0216	0.5462	1.0216	1.0108
No log	6.9231	90	1.0302	0.5601	1.0302	1.0150
No log	7.0769	92	1.0255	0.5601	1.0255	1.0127
No log	7.2308	94	1.0372	0.5082	1.0372	1.0184
No log	7.3846	96	1.0461	0.5067	1.0461	1.0228
No log	7.5385	98	1.0610	0.5067	1.0610	1.0301
No log	7.6923	100	1.0750	0.4933	1.0750	1.0368
No log	7.8462	102	1.0843	0.4933	1.0843	1.0413
No log	8.0	104	1.0914	0.4933	1.0914	1.0447
No log	8.1538	106	1.0905	0.4933	1.0905	1.0443
No log	8.3077	108	1.0880	0.4933	1.0880	1.0431
No log	8.4615	110	1.0890	0.4933	1.0890	1.0435
No log	8.6154	112	1.0865	0.4933	1.0865	1.0424
No log	8.7692	114	1.0780	0.4933	1.0780	1.0383
No log	8.9231	116	1.0789	0.4933	1.0789	1.0387
No log	9.0769	118	1.0787	0.4798	1.0787	1.0386
No log	9.2308	120	1.0701	0.4798	1.0701	1.0344
No log	9.3846	122	1.0583	0.4798	1.0583	1.0287
No log	9.5385	124	1.0499	0.4933	1.0499	1.0247
No log	9.6923	126	1.0453	0.4933	1.0453	1.0224
No log	9.8462	128	1.0424	0.4933	1.0424	1.0210
No log	10.0	130	1.0411	0.4933	1.0411	1.0203

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/ArabicNewSplits3_FineTuningAraBERT_run2_AugV5_k2_task1_organization

ArabicNewSplits3_FineTuningAraBERT_run2_AugV5_k2_task1_organization

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
ArabicNewSplits3_FineTuningAraBERT_run2_AugV5_k2_task1_organization