ArabicNewSplits6_FineTuningAraBERT_run1_AugV5_k9_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: 1.1555
• Qwk: 0.5710
• Mse: 1.1555
• Rmse: 1.0750

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	0.0588	2	2.2822	0.0049	2.2822	1.5107
No log	0.1176	4	1.5728	0.0891	1.5728	1.2541
No log	0.1765	6	1.5450	0.1423	1.5450	1.2430
No log	0.2353	8	1.6683	0.1714	1.6683	1.2916
No log	0.2941	10	1.5273	0.2025	1.5273	1.2358
No log	0.3529	12	1.4477	0.1994	1.4477	1.2032
No log	0.4118	14	1.5719	0.2761	1.5719	1.2538
No log	0.4706	16	1.6023	0.2907	1.6023	1.2658
No log	0.5294	18	1.5269	0.2468	1.5269	1.2357
No log	0.5882	20	1.7283	0.3071	1.7283	1.3146
No log	0.6471	22	2.0613	0.2146	2.0613	1.4357
No log	0.7059	24	1.9321	0.2825	1.9321	1.3900
No log	0.7647	26	1.4661	0.2731	1.4661	1.2108
No log	0.8235	28	1.2814	0.2304	1.2814	1.1320
No log	0.8824	30	1.2823	0.2786	1.2823	1.1324
No log	0.9412	32	1.2427	0.2766	1.2427	1.1148
No log	1.0	34	1.2212	0.1810	1.2212	1.1051
No log	1.0588	36	1.3178	0.1841	1.3178	1.1480
No log	1.1176	38	1.5492	0.3449	1.5492	1.2447
No log	1.1765	40	1.8254	0.2358	1.8254	1.3511
No log	1.2353	42	1.8937	0.1820	1.8937	1.3761
No log	1.2941	44	1.8081	0.1311	1.8081	1.3447
No log	1.3529	46	1.7038	0.1069	1.7038	1.3053
No log	1.4118	48	1.6960	0.1403	1.6960	1.3023
No log	1.4706	50	1.6290	0.2176	1.6290	1.2763
No log	1.5294	52	1.3992	0.3038	1.3992	1.1829
No log	1.5882	54	1.3177	0.3698	1.3177	1.1479
No log	1.6471	56	1.4900	0.3626	1.4900	1.2207
No log	1.7059	58	1.8616	0.3162	1.8616	1.3644
No log	1.7647	60	1.6929	0.3536	1.6929	1.3011
No log	1.8235	62	1.3657	0.3659	1.3657	1.1686
No log	1.8824	64	1.1902	0.3841	1.1902	1.0910
No log	1.9412	66	1.1617	0.3324	1.1617	1.0778
No log	2.0	68	1.2535	0.3989	1.2535	1.1196
No log	2.0588	70	1.5339	0.3862	1.5339	1.2385
No log	2.1176	72	1.5255	0.3950	1.5255	1.2351
No log	2.1765	74	1.7148	0.3852	1.7148	1.3095
No log	2.2353	76	1.8379	0.3291	1.8379	1.3557
No log	2.2941	78	1.6841	0.3877	1.6841	1.2977
No log	2.3529	80	1.4745	0.4185	1.4745	1.2143
No log	2.4118	82	1.3330	0.4411	1.3330	1.1546
No log	2.4706	84	1.2123	0.4569	1.2123	1.1011
No log	2.5294	86	1.2655	0.4561	1.2655	1.1249
No log	2.5882	88	1.4675	0.4148	1.4675	1.2114
No log	2.6471	90	1.3935	0.4198	1.3935	1.1805
No log	2.7059	92	1.2077	0.4860	1.2077	1.0990
No log	2.7647	94	1.2078	0.4904	1.2078	1.0990
No log	2.8235	96	1.3400	0.4620	1.3400	1.1576
No log	2.8824	98	1.5249	0.4448	1.5249	1.2348
No log	2.9412	100	1.5166	0.4408	1.5166	1.2315
No log	3.0	102	1.1875	0.4654	1.1875	1.0897
No log	3.0588	104	1.0275	0.5017	1.0275	1.0137
No log	3.1176	106	1.0399	0.4931	1.0399	1.0198
No log	3.1765	108	1.1358	0.4817	1.1358	1.0657
No log	3.2353	110	1.1478	0.5383	1.1478	1.0713
No log	3.2941	112	1.1538	0.5483	1.1538	1.0741
No log	3.3529	114	1.0638	0.5638	1.0638	1.0314
No log	3.4118	116	1.0037	0.5814	1.0037	1.0018
No log	3.4706	118	1.0016	0.5737	1.0016	1.0008
No log	3.5294	120	1.0007	0.5737	1.0007	1.0004
No log	3.5882	122	1.1096	0.5261	1.1096	1.0534
No log	3.6471	124	1.2973	0.4765	1.2973	1.1390
No log	3.7059	126	1.3333	0.4510	1.3333	1.1547
No log	3.7647	128	1.2326	0.4698	1.2326	1.1102
No log	3.8235	130	1.1792	0.4896	1.1792	1.0859
No log	3.8824	132	1.2438	0.4520	1.2438	1.1152
No log	3.9412	134	1.2335	0.4482	1.2335	1.1106
No log	4.0	136	1.1734	0.4644	1.1734	1.0832
No log	4.0588	138	1.1485	0.4431	1.1485	1.0717
No log	4.1176	140	1.1450	0.4619	1.1450	1.0701
No log	4.1765	142	1.0836	0.4994	1.0836	1.0410
No log	4.2353	144	1.1126	0.5128	1.1126	1.0548
No log	4.2941	146	1.2490	0.4733	1.2490	1.1176
No log	4.3529	148	1.2726	0.4680	1.2726	1.1281
No log	4.4118	150	1.2475	0.4941	1.2475	1.1169
No log	4.4706	152	1.0775	0.5435	1.0775	1.0380
No log	4.5294	154	1.0345	0.5510	1.0345	1.0171
No log	4.5882	156	1.0791	0.5485	1.0791	1.0388
No log	4.6471	158	1.2065	0.4865	1.2065	1.0984
No log	4.7059	160	1.3218	0.4833	1.3218	1.1497
No log	4.7647	162	1.2374	0.4848	1.2374	1.1124
No log	4.8235	164	1.0412	0.5703	1.0412	1.0204
No log	4.8824	166	0.9716	0.5872	0.9716	0.9857
No log	4.9412	168	0.9884	0.5812	0.9884	0.9942
No log	5.0	170	1.1434	0.5700	1.1434	1.0693
No log	5.0588	172	1.3990	0.5010	1.3990	1.1828
No log	5.1176	174	1.4330	0.5004	1.4330	1.1971
No log	5.1765	176	1.2234	0.5371	1.2234	1.1061
No log	5.2353	178	0.9743	0.5827	0.9743	0.9871
No log	5.2941	180	0.8896	0.5910	0.8896	0.9432
No log	5.3529	182	0.8906	0.5410	0.8906	0.9437
No log	5.4118	184	0.9379	0.5977	0.9379	0.9685
No log	5.4706	186	1.0472	0.5567	1.0472	1.0233
No log	5.5294	188	1.1859	0.5153	1.1859	1.0890
No log	5.5882	190	1.2335	0.5106	1.2335	1.1106
No log	5.6471	192	1.2013	0.5106	1.2013	1.0960
No log	5.7059	194	1.1886	0.4909	1.1886	1.0903
No log	5.7647	196	1.1094	0.5220	1.1094	1.0533
No log	5.8235	198	1.0237	0.5777	1.0237	1.0118
No log	5.8824	200	1.0124	0.5668	1.0124	1.0062
No log	5.9412	202	1.0609	0.5582	1.0609	1.0300
No log	6.0	204	1.2110	0.5322	1.2110	1.1004
No log	6.0588	206	1.4056	0.4893	1.4056	1.1856
No log	6.1176	208	1.4971	0.4534	1.4971	1.2236
No log	6.1765	210	1.4690	0.4542	1.4690	1.2120
No log	6.2353	212	1.3236	0.4556	1.3236	1.1505
No log	6.2941	214	1.1283	0.5515	1.1283	1.0622
No log	6.3529	216	1.0082	0.5983	1.0082	1.0041
No log	6.4118	218	0.9939	0.5944	0.9939	0.9970
No log	6.4706	220	1.0381	0.5905	1.0381	1.0189
No log	6.5294	222	1.1513	0.5522	1.1513	1.0730
No log	6.5882	224	1.2370	0.5012	1.2370	1.1122
No log	6.6471	226	1.1980	0.5243	1.1980	1.0946
No log	6.7059	228	1.1023	0.5461	1.1023	1.0499
No log	6.7647	230	1.0153	0.5925	1.0153	1.0076
No log	6.8235	232	1.0154	0.5852	1.0154	1.0077
No log	6.8824	234	1.0428	0.5925	1.0428	1.0212
No log	6.9412	236	1.0856	0.5550	1.0856	1.0419
No log	7.0	238	1.1719	0.5232	1.1719	1.0825
No log	7.0588	240	1.1925	0.5131	1.1925	1.0920
No log	7.1176	242	1.1786	0.5097	1.1786	1.0856
No log	7.1765	244	1.1115	0.5294	1.1115	1.0543
No log	7.2353	246	1.0795	0.5791	1.0795	1.0390
No log	7.2941	248	1.0715	0.5630	1.0715	1.0351
No log	7.3529	250	1.0835	0.5494	1.0835	1.0409
No log	7.4118	252	1.1435	0.5574	1.1435	1.0693
No log	7.4706	254	1.2553	0.5223	1.2553	1.1204
No log	7.5294	256	1.3456	0.5102	1.3456	1.1600
No log	7.5882	258	1.3437	0.5109	1.3437	1.1592
No log	7.6471	260	1.2789	0.5109	1.2789	1.1309
No log	7.7059	262	1.1820	0.5418	1.1820	1.0872
No log	7.7647	264	1.1069	0.5527	1.1069	1.0521
No log	7.8235	266	1.0795	0.5634	1.0795	1.0390
No log	7.8824	268	1.0821	0.5670	1.0821	1.0402
No log	7.9412	270	1.1162	0.5527	1.1162	1.0565
No log	8.0	272	1.1736	0.5547	1.1736	1.0833
No log	8.0588	274	1.2461	0.5290	1.2461	1.1163
No log	8.1176	276	1.2868	0.4988	1.2868	1.1344
No log	8.1765	278	1.2863	0.4988	1.2863	1.1342
No log	8.2353	280	1.2424	0.5128	1.2424	1.1146
No log	8.2941	282	1.1821	0.5385	1.1821	1.0873
No log	8.3529	284	1.1278	0.5651	1.1278	1.0620
No log	8.4118	286	1.0952	0.5555	1.0952	1.0465
No log	8.4706	288	1.0735	0.5428	1.0735	1.0361
No log	8.5294	290	1.0803	0.5334	1.0803	1.0394
No log	8.5882	292	1.1108	0.5580	1.1108	1.0539
No log	8.6471	294	1.1408	0.5512	1.1408	1.0681
No log	8.7059	296	1.1481	0.5512	1.1481	1.0715
No log	8.7647	298	1.1663	0.5517	1.1663	1.0800
No log	8.8235	300	1.1932	0.5377	1.1932	1.0924
No log	8.8824	302	1.2098	0.5290	1.2098	1.0999
No log	8.9412	304	1.2293	0.5290	1.2293	1.1087
No log	9.0	306	1.2378	0.5246	1.2378	1.1126
No log	9.0588	308	1.2403	0.5274	1.2403	1.1137
No log	9.1176	310	1.2192	0.5290	1.2192	1.1042
No log	9.1765	312	1.1986	0.5377	1.1986	1.0948
No log	9.2353	314	1.1859	0.5632	1.1859	1.0890
No log	9.2941	316	1.1761	0.5598	1.1761	1.0845
No log	9.3529	318	1.1735	0.5598	1.1735	1.0833
No log	9.4118	320	1.1719	0.5688	1.1719	1.0825
No log	9.4706	322	1.1722	0.5598	1.1722	1.0827
No log	9.5294	324	1.1696	0.5688	1.1696	1.0815
No log	9.5882	326	1.1719	0.5598	1.1719	1.0826
No log	9.6471	328	1.1768	0.5632	1.1768	1.0848
No log	9.7059	330	1.1747	0.5632	1.1747	1.0838
No log	9.7647	332	1.1680	0.5583	1.1680	1.0807
No log	9.8235	334	1.1627	0.5583	1.1627	1.0783
No log	9.8824	336	1.1583	0.5710	1.1583	1.0762
No log	9.9412	338	1.1561	0.5710	1.1561	1.0752
No log	10.0	340	1.1555	0.5710	1.1555	1.0750

Framework versions

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