ArabicNewSplits6_FineTuningAraBERT_run1_AugV5_k8_task5_organization

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.0598
• Qwk: 0.6244
• Mse: 1.0598
• Rmse: 1.0295

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.0625	2	2.1160	0.0338	2.1160	1.4547
No log	0.125	4	1.7149	0.0173	1.7149	1.3095
No log	0.1875	6	1.5435	0.1512	1.5435	1.2424
No log	0.25	8	1.5400	0.1549	1.5400	1.2410
No log	0.3125	10	1.4927	0.1968	1.4927	1.2218
No log	0.375	12	1.3635	0.1841	1.3635	1.1677
No log	0.4375	14	1.3708	0.1762	1.3708	1.1708
No log	0.5	16	1.4699	0.2619	1.4699	1.2124
No log	0.5625	18	1.4411	0.2231	1.4411	1.2005
No log	0.625	20	1.4930	0.2971	1.4930	1.2219
No log	0.6875	22	1.5629	0.3682	1.5629	1.2502
No log	0.75	24	1.3694	0.3425	1.3694	1.1702
No log	0.8125	26	1.2128	0.2598	1.2128	1.1013
No log	0.875	28	1.1703	0.3543	1.1703	1.0818
No log	0.9375	30	1.2999	0.3972	1.2999	1.1401
No log	1.0	32	1.3924	0.3710	1.3924	1.1800
No log	1.0625	34	1.3020	0.2762	1.3020	1.1411
No log	1.125	36	1.2648	0.2688	1.2648	1.1246
No log	1.1875	38	1.2388	0.2788	1.2388	1.1130
No log	1.25	40	1.2131	0.3308	1.2131	1.1014
No log	1.3125	42	1.2511	0.3752	1.2511	1.1185
No log	1.375	44	1.3116	0.3878	1.3116	1.1452
No log	1.4375	46	1.1461	0.3954	1.1461	1.0705
No log	1.5	48	1.1193	0.3518	1.1193	1.0580
No log	1.5625	50	1.1570	0.3000	1.1570	1.0756
No log	1.625	52	1.1027	0.4247	1.1027	1.0501
No log	1.6875	54	1.1867	0.3924	1.1867	1.0894
No log	1.75	56	1.3662	0.4179	1.3662	1.1688
No log	1.8125	58	1.5288	0.4253	1.5288	1.2364
No log	1.875	60	1.4065	0.4217	1.4065	1.1860
No log	1.9375	62	1.3380	0.3856	1.3380	1.1567
No log	2.0	64	1.2551	0.3348	1.2551	1.1203
No log	2.0625	66	1.2275	0.3342	1.2275	1.1079
No log	2.125	68	1.2083	0.3618	1.2083	1.0992
No log	2.1875	70	1.1736	0.3781	1.1736	1.0833
No log	2.25	72	1.1812	0.3571	1.1812	1.0868
No log	2.3125	74	1.3866	0.4122	1.3866	1.1775
No log	2.375	76	1.7880	0.3745	1.7880	1.3371
No log	2.4375	78	1.8774	0.3438	1.8774	1.3702
No log	2.5	80	1.6678	0.4008	1.6678	1.2914
No log	2.5625	82	1.2519	0.4263	1.2519	1.1189
No log	2.625	84	0.9911	0.4967	0.9911	0.9955
No log	2.6875	86	0.9727	0.5044	0.9727	0.9863
No log	2.75	88	1.0008	0.4998	1.0008	1.0004
No log	2.8125	90	1.1540	0.4583	1.1540	1.0743
No log	2.875	92	1.2910	0.4718	1.2910	1.1362
No log	2.9375	94	1.2923	0.5139	1.2923	1.1368
No log	3.0	96	1.2713	0.5100	1.2713	1.1275
No log	3.0625	98	1.2018	0.5158	1.2018	1.0963
No log	3.125	100	1.0483	0.5181	1.0483	1.0239
No log	3.1875	102	0.9996	0.5920	0.9996	0.9998
No log	3.25	104	0.9521	0.5739	0.9521	0.9758
No log	3.3125	106	1.0000	0.6311	1.0000	1.0000
No log	3.375	108	1.0410	0.5954	1.0410	1.0203
No log	3.4375	110	1.1661	0.5928	1.1661	1.0799
No log	3.5	112	1.3165	0.5436	1.3165	1.1474
No log	3.5625	114	1.2606	0.5725	1.2606	1.1228
No log	3.625	116	1.0182	0.6535	1.0182	1.0091
No log	3.6875	118	1.0135	0.6687	1.0135	1.0067
No log	3.75	120	1.2348	0.5850	1.2348	1.1112
No log	3.8125	122	1.4966	0.5372	1.4966	1.2234
No log	3.875	124	1.4780	0.5093	1.4780	1.2157
No log	3.9375	126	1.1891	0.5844	1.1891	1.0904
No log	4.0	128	0.9673	0.6604	0.9673	0.9835
No log	4.0625	130	0.9407	0.6562	0.9407	0.9699
No log	4.125	132	1.0966	0.6209	1.0966	1.0472
No log	4.1875	134	1.4173	0.5064	1.4173	1.1905
No log	4.25	136	1.5827	0.4404	1.5827	1.2581
No log	4.3125	138	1.4817	0.5004	1.4817	1.2173
No log	4.375	140	1.1771	0.5476	1.1771	1.0849
No log	4.4375	142	1.0183	0.6183	1.0183	1.0091
No log	4.5	144	1.0389	0.6054	1.0389	1.0192
No log	4.5625	146	1.2676	0.5650	1.2676	1.1259
No log	4.625	148	1.3956	0.5444	1.3956	1.1813
No log	4.6875	150	1.1840	0.5864	1.1840	1.0881
No log	4.75	152	0.9527	0.5974	0.9527	0.9761
No log	4.8125	154	0.8234	0.6385	0.8234	0.9074
No log	4.875	156	0.8268	0.6618	0.8268	0.9093
No log	4.9375	158	1.0407	0.6309	1.0407	1.0201
No log	5.0	160	1.2163	0.5851	1.2163	1.1029
No log	5.0625	162	1.1730	0.5914	1.1730	1.0830
No log	5.125	164	0.9633	0.6695	0.9633	0.9815
No log	5.1875	166	0.7776	0.6983	0.7776	0.8818
No log	5.25	168	0.7579	0.7010	0.7579	0.8706
No log	5.3125	170	0.8281	0.6936	0.8281	0.9100
No log	5.375	172	0.9615	0.6535	0.9615	0.9806
No log	5.4375	174	1.1690	0.5765	1.1690	1.0812
No log	5.5	176	1.4377	0.5532	1.4377	1.1990
No log	5.5625	178	1.5359	0.5345	1.5359	1.2393
No log	5.625	180	1.4487	0.5488	1.4487	1.2036
No log	5.6875	182	1.2129	0.5583	1.2129	1.1013
No log	5.75	184	0.9592	0.6300	0.9592	0.9794
No log	5.8125	186	0.8294	0.6328	0.8294	0.9107
No log	5.875	188	0.8175	0.6314	0.8175	0.9041
No log	5.9375	190	0.9013	0.6381	0.9013	0.9494
No log	6.0	192	1.0476	0.6244	1.0476	1.0235
No log	6.0625	194	1.0476	0.6332	1.0476	1.0235
No log	6.125	196	1.0477	0.6332	1.0477	1.0236
No log	6.1875	198	0.9526	0.6258	0.9526	0.9760
No log	6.25	200	0.8349	0.6260	0.8349	0.9137
No log	6.3125	202	0.8625	0.6280	0.8625	0.9287
No log	6.375	204	0.9954	0.6231	0.9954	0.9977
No log	6.4375	206	1.2755	0.5981	1.2755	1.1294
No log	6.5	208	1.6464	0.5150	1.6464	1.2831
No log	6.5625	210	1.7519	0.5139	1.7519	1.3236
No log	6.625	212	1.6424	0.5062	1.6424	1.2815
No log	6.6875	214	1.3614	0.5718	1.3614	1.1668
No log	6.75	216	1.0455	0.6172	1.0455	1.0225
No log	6.8125	218	0.8458	0.5650	0.8458	0.9197
No log	6.875	220	0.8072	0.5882	0.8072	0.8984
No log	6.9375	222	0.8263	0.5868	0.8263	0.9090
No log	7.0	224	0.9171	0.5853	0.9171	0.9576
No log	7.0625	226	1.1117	0.6086	1.1117	1.0544
No log	7.125	228	1.3619	0.5397	1.3619	1.1670
No log	7.1875	230	1.4428	0.5450	1.4428	1.2012
No log	7.25	232	1.3831	0.5434	1.3831	1.1761
No log	7.3125	234	1.2284	0.5555	1.2284	1.1083
No log	7.375	236	1.1368	0.5826	1.1368	1.0662
No log	7.4375	238	1.0245	0.6374	1.0245	1.0122
No log	7.5	240	0.9635	0.6325	0.9635	0.9816
No log	7.5625	242	0.9304	0.6334	0.9304	0.9646
No log	7.625	244	0.9288	0.6290	0.9288	0.9637
No log	7.6875	246	0.9509	0.6325	0.9509	0.9752
No log	7.75	248	1.0050	0.6114	1.0050	1.0025
No log	7.8125	250	1.0902	0.6216	1.0902	1.0441
No log	7.875	252	1.1132	0.6128	1.1132	1.0551
No log	7.9375	254	1.1418	0.6232	1.1418	1.0685
No log	8.0	256	1.1174	0.6217	1.1174	1.0571
No log	8.0625	258	1.0556	0.6216	1.0556	1.0274
No log	8.125	260	1.0642	0.6216	1.0642	1.0316
No log	8.1875	262	1.1095	0.6128	1.1095	1.0533
No log	8.25	264	1.1037	0.6128	1.1037	1.0505
No log	8.3125	266	1.0671	0.6216	1.0671	1.0330
No log	8.375	268	1.0271	0.6216	1.0271	1.0135
No log	8.4375	270	1.0096	0.6215	1.0096	1.0048
No log	8.5	272	0.9813	0.6052	0.9813	0.9906
No log	8.5625	274	0.9734	0.6052	0.9734	0.9866
No log	8.625	276	0.9950	0.6185	0.9950	0.9975
No log	8.6875	278	1.0081	0.6185	1.0081	1.0040
No log	8.75	280	1.0417	0.6172	1.0417	1.0206
No log	8.8125	282	1.0967	0.6002	1.0967	1.0472
No log	8.875	284	1.1329	0.6002	1.1329	1.0644
No log	8.9375	286	1.1632	0.5905	1.1632	1.0785
No log	9.0	288	1.1566	0.5905	1.1566	1.0755
No log	9.0625	290	1.1302	0.6020	1.1302	1.0631
No log	9.125	292	1.0973	0.6103	1.0973	1.0475
No log	9.1875	294	1.0484	0.6244	1.0484	1.0239
No log	9.25	296	1.0168	0.6244	1.0168	1.0084
No log	9.3125	298	1.0013	0.6243	1.0013	1.0007
No log	9.375	300	1.0105	0.6243	1.0105	1.0053
No log	9.4375	302	1.0362	0.6244	1.0362	1.0180
No log	9.5	304	1.0549	0.6244	1.0549	1.0271
No log	9.5625	306	1.0620	0.6231	1.0620	1.0305
No log	9.625	308	1.0737	0.6231	1.0737	1.0362
No log	9.6875	310	1.0833	0.6144	1.0833	1.0408
No log	9.75	312	1.0802	0.6144	1.0802	1.0393
No log	9.8125	314	1.0740	0.6231	1.0740	1.0363
No log	9.875	316	1.0679	0.6244	1.0679	1.0334
No log	9.9375	318	1.0628	0.6244	1.0628	1.0309
No log	10.0	320	1.0598	0.6244	1.0598	1.0295

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu118
• Datasets 2.21.0
• Tokenizers 0.19.1