Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.1818	2	2.5300	0.1733	2.5300	1.5906
No log	0.3636	4	1.7812	0.0836	1.7812	1.3346
No log	0.5455	6	1.5012	0.0165	1.5012	1.2252
No log	0.7273	8	1.3442	0.1305	1.3442	1.1594
No log	0.9091	10	1.3540	0.1729	1.3540	1.1636
No log	1.0909	12	1.3156	0.1418	1.3156	1.1470
No log	1.2727	14	1.2819	0.1418	1.2819	1.1322
No log	1.4545	16	1.2649	0.1766	1.2649	1.1247
No log	1.6364	18	1.2432	0.1418	1.2432	1.1150
No log	1.8182	20	1.2627	0.1418	1.2627	1.1237
No log	2.0	22	1.3403	0.1326	1.3403	1.1577
No log	2.1818	24	1.4135	0.1212	1.4135	1.1889
No log	2.3636	26	1.4925	0.3378	1.4925	1.2217
No log	2.5455	28	1.5658	0.3296	1.5658	1.2513
No log	2.7273	30	1.5778	0.3580	1.5778	1.2561
No log	2.9091	32	1.5097	0.2498	1.5097	1.2287
No log	3.0909	34	1.4836	0.2083	1.4836	1.2180
No log	3.2727	36	1.5224	0.3697	1.5224	1.2338
No log	3.4545	38	1.5347	0.3407	1.5347	1.2388
No log	3.6364	40	1.4941	0.2605	1.4941	1.2223
No log	3.8182	42	1.4730	0.2083	1.4730	1.2137
No log	4.0	44	1.4518	0.1616	1.4518	1.2049
No log	4.1818	46	1.4177	0.2020	1.4177	1.1907
No log	4.3636	48	1.3923	0.1782	1.3923	1.1800
No log	4.5455	50	1.3945	0.2222	1.3945	1.1809
No log	4.7273	52	1.4037	0.2449	1.4037	1.1848
No log	4.9091	54	1.4231	0.3489	1.4231	1.1929
No log	5.0909	56	1.4893	0.3386	1.4893	1.2204
No log	5.2727	58	1.5326	0.3428	1.5326	1.2380
No log	5.4545	60	1.5264	0.4169	1.5264	1.2355
No log	5.6364	62	1.5175	0.4228	1.5175	1.2319
No log	5.8182	64	1.5574	0.3931	1.5574	1.2480
No log	6.0	66	1.6494	0.3411	1.6494	1.2843
No log	6.1818	68	1.7818	0.3301	1.7818	1.3348
No log	6.3636	70	1.8253	0.3058	1.8253	1.3510
No log	6.5455	72	1.7581	0.3294	1.7581	1.3259
No log	6.7273	74	1.7033	0.3208	1.7033	1.3051
No log	6.9091	76	1.6849	0.3330	1.6849	1.2981
No log	7.0909	78	1.6153	0.3444	1.6153	1.2709
No log	7.2727	80	1.6617	0.3456	1.6617	1.2891
No log	7.4545	82	1.8027	0.3097	1.8027	1.3427
No log	7.6364	84	1.9454	0.2524	1.9454	1.3948
No log	7.8182	86	2.0545	0.2280	2.0545	1.4334
No log	8.0	88	2.0672	0.2418	2.0672	1.4378
No log	8.1818	90	2.0462	0.2418	2.0462	1.4305
No log	8.3636	92	1.9775	0.2632	1.9775	1.4062
No log	8.5455	94	1.8833	0.2980	1.8833	1.3723
No log	8.7273	96	1.7957	0.3216	1.7957	1.3400
No log	8.9091	98	1.7590	0.3208	1.7590	1.3263
No log	9.0909	100	1.7751	0.3216	1.7751	1.3323
No log	9.2727	102	1.7767	0.3216	1.7767	1.3329
No log	9.4545	104	1.7922	0.3216	1.7922	1.3387
No log	9.6364	106	1.8047	0.3216	1.8047	1.3434
No log	9.8182	108	1.8160	0.3216	1.8160	1.3476
No log	10.0	110	1.8211	0.3216	1.8211	1.3495

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1

MayBashendy/ArabicNewSplits_FineTuningAraBERT_AugV5_k4_task5_organization_fold1

ArabicNewSplits_FineTuningAraBERT_AugV5_k4_task5_organization_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MayBashendy/
ArabicNewSplits_FineTuningAraBERT_AugV5_k4_task5_organization_fold1