ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k6_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: 1.0284
• Qwk: 0.5856
• Mse: 1.0284
• Rmse: 1.0141

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	0.0667	2	2.2830	0.0429	2.2830	1.5110
No log	0.1333	4	1.5811	0.1810	1.5811	1.2574
No log	0.2	6	1.4044	0.1688	1.4044	1.1851
No log	0.2667	8	1.3701	0.2045	1.3701	1.1705
No log	0.3333	10	1.3227	0.2234	1.3227	1.1501
No log	0.4	12	1.3059	0.2099	1.3059	1.1428
No log	0.4667	14	1.3776	0.2825	1.3776	1.1737
No log	0.5333	16	1.5161	0.3399	1.5161	1.2313
No log	0.6	18	1.4013	0.3466	1.4013	1.1838
No log	0.6667	20	1.2033	0.2904	1.2033	1.0970
No log	0.7333	22	1.3912	0.2375	1.3912	1.1795
No log	0.8	24	1.3669	0.3144	1.3669	1.1691
No log	0.8667	26	1.2450	0.3846	1.2450	1.1158
No log	0.9333	28	1.1719	0.3242	1.1719	1.0825
No log	1.0	30	1.2235	0.2401	1.2235	1.1061
No log	1.0667	32	1.4118	0.3060	1.4118	1.1882
No log	1.1333	34	1.4894	0.2929	1.4894	1.2204
No log	1.2	36	1.3810	0.1317	1.3810	1.1752
No log	1.2667	38	1.2878	0.1079	1.2878	1.1348
No log	1.3333	40	1.2141	0.2406	1.2141	1.1019
No log	1.4	42	1.1477	0.3421	1.1477	1.0713
No log	1.4667	44	1.1135	0.3669	1.1135	1.0552
No log	1.5333	46	1.0981	0.3741	1.0981	1.0479
No log	1.6	48	1.1224	0.3514	1.1224	1.0594
No log	1.6667	50	1.0722	0.3562	1.0722	1.0354
No log	1.7333	52	1.0162	0.4883	1.0162	1.0081
No log	1.8	54	1.0281	0.4769	1.0281	1.0139
No log	1.8667	56	1.0941	0.4850	1.0941	1.0460
No log	1.9333	58	1.1884	0.4595	1.1884	1.0901
No log	2.0	60	1.1850	0.4376	1.1850	1.0886
No log	2.0667	62	1.0727	0.4972	1.0727	1.0357
No log	2.1333	64	0.9873	0.5287	0.9873	0.9937
No log	2.2	66	1.0742	0.4291	1.0742	1.0364
No log	2.2667	68	1.0813	0.3963	1.0813	1.0398
No log	2.3333	70	0.9915	0.4728	0.9915	0.9957
No log	2.4	72	1.0091	0.5190	1.0091	1.0045
No log	2.4667	74	1.2618	0.4663	1.2618	1.1233
No log	2.5333	76	1.6436	0.4204	1.6436	1.2820
No log	2.6	78	1.7873	0.3867	1.7873	1.3369
No log	2.6667	80	1.7030	0.4011	1.7030	1.3050
No log	2.7333	82	1.4577	0.4424	1.4577	1.2073
No log	2.8	84	1.2948	0.4279	1.2948	1.1379
No log	2.8667	86	1.2070	0.4670	1.2070	1.0986
No log	2.9333	88	1.1124	0.4666	1.1124	1.0547
No log	3.0	90	1.0523	0.5200	1.0523	1.0258
No log	3.0667	92	1.0527	0.5355	1.0527	1.0260
No log	3.1333	94	1.1631	0.5072	1.1631	1.0785
No log	3.2	96	1.4167	0.5092	1.4167	1.1903
No log	3.2667	98	1.5067	0.5024	1.5067	1.2275
No log	3.3333	100	1.3997	0.5218	1.3997	1.1831
No log	3.4	102	1.3023	0.5480	1.3023	1.1412
No log	3.4667	104	1.2230	0.5547	1.2230	1.1059
No log	3.5333	106	1.2489	0.5405	1.2489	1.1175
No log	3.6	108	1.3939	0.5487	1.3939	1.1807
No log	3.6667	110	1.4439	0.5265	1.4439	1.2016
No log	3.7333	112	1.5158	0.5154	1.5158	1.2312
No log	3.8	114	1.5420	0.5248	1.5420	1.2418
No log	3.8667	116	1.3854	0.5208	1.3854	1.1770
No log	3.9333	118	1.2496	0.5326	1.2496	1.1178
No log	4.0	120	1.0607	0.5159	1.0607	1.0299
No log	4.0667	122	0.9353	0.5427	0.9353	0.9671
No log	4.1333	124	0.8748	0.6078	0.8748	0.9353
No log	4.2	126	0.8577	0.5927	0.8577	0.9261
No log	4.2667	128	0.9010	0.5910	0.9010	0.9492
No log	4.3333	130	0.9717	0.6222	0.9717	0.9857
No log	4.4	132	0.9754	0.6338	0.9754	0.9876
No log	4.4667	134	0.9181	0.6247	0.9181	0.9582
No log	4.5333	136	0.8482	0.6411	0.8482	0.9210
No log	4.6	138	0.8691	0.6382	0.8691	0.9323
No log	4.6667	140	0.9461	0.5808	0.9461	0.9727
No log	4.7333	142	1.1049	0.5570	1.1049	1.0511
No log	4.8	144	1.2206	0.5396	1.2206	1.1048
No log	4.8667	146	1.3270	0.5351	1.3270	1.1519
No log	4.9333	148	1.3154	0.5455	1.3154	1.1469
No log	5.0	150	1.2226	0.5471	1.2226	1.1057
No log	5.0667	152	1.1036	0.5638	1.1036	1.0505
No log	5.1333	154	1.0505	0.5600	1.0505	1.0249
No log	5.2	156	1.0325	0.5680	1.0325	1.0161
No log	5.2667	158	1.0045	0.5806	1.0045	1.0022
No log	5.3333	160	1.0267	0.5806	1.0267	1.0132
No log	5.4	162	1.1405	0.5456	1.1405	1.0680
No log	5.4667	164	1.2289	0.5225	1.2289	1.1086
No log	5.5333	166	1.1927	0.5274	1.1927	1.0921
No log	5.6	168	1.1006	0.5843	1.1006	1.0491
No log	5.6667	170	0.9632	0.6468	0.9632	0.9814
No log	5.7333	172	0.8709	0.6426	0.8709	0.9332
No log	5.8	174	0.8506	0.6387	0.8506	0.9223
No log	5.8667	176	0.8581	0.6457	0.8581	0.9263
No log	5.9333	178	0.9243	0.6744	0.9243	0.9614
No log	6.0	180	0.9902	0.6172	0.9902	0.9951
No log	6.0667	182	1.0721	0.5911	1.0721	1.0354
No log	6.1333	184	1.0869	0.6000	1.0869	1.0425
No log	6.2	186	1.0542	0.5911	1.0542	1.0268
No log	6.2667	188	0.9499	0.6358	0.9499	0.9746
No log	6.3333	190	0.8510	0.6746	0.8510	0.9225
No log	6.4	192	0.8210	0.6678	0.8210	0.9061
No log	6.4667	194	0.8353	0.6775	0.8353	0.9139
No log	6.5333	196	0.9151	0.6543	0.9151	0.9566
No log	6.6	198	1.0350	0.5901	1.0350	1.0174
No log	6.6667	200	1.1586	0.5789	1.1586	1.0764
No log	6.7333	202	1.1807	0.5716	1.1807	1.0866
No log	6.8	204	1.1231	0.5513	1.1231	1.0597
No log	6.8667	206	1.1063	0.5513	1.1063	1.0518
No log	6.9333	208	1.0975	0.5487	1.0975	1.0476
No log	7.0	210	1.0695	0.5586	1.0695	1.0342
No log	7.0667	212	1.0841	0.5606	1.0841	1.0412
No log	7.1333	214	1.1074	0.5712	1.1074	1.0523
No log	7.2	216	1.1624	0.5604	1.1624	1.0782
No log	7.2667	218	1.1647	0.5604	1.1647	1.0792
No log	7.3333	220	1.1350	0.5690	1.1350	1.0654
No log	7.4	222	1.0883	0.5758	1.0883	1.0432
No log	7.4667	224	1.0372	0.5735	1.0372	1.0184
No log	7.5333	226	0.9913	0.5537	0.9913	0.9957
No log	7.6	228	0.9597	0.5838	0.9597	0.9796
No log	7.6667	230	0.9550	0.5940	0.9550	0.9772
No log	7.7333	232	0.9627	0.5940	0.9627	0.9812
No log	7.8	234	0.9941	0.6137	0.9941	0.9970
No log	7.8667	236	1.0353	0.6101	1.0353	1.0175
No log	7.9333	238	1.0679	0.5824	1.0679	1.0334
No log	8.0	240	1.0604	0.5879	1.0604	1.0298
No log	8.0667	242	1.0300	0.5768	1.0300	1.0149
No log	8.1333	244	0.9973	0.5803	0.9973	0.9987
No log	8.2	246	1.0001	0.5791	1.0001	1.0000
No log	8.2667	248	1.0038	0.5893	1.0038	1.0019
No log	8.3333	250	1.0009	0.5893	1.0009	1.0004
No log	8.4	252	0.9869	0.5768	0.9869	0.9934
No log	8.4667	254	0.9619	0.6062	0.9619	0.9807
No log	8.5333	256	0.9601	0.6062	0.9601	0.9799
No log	8.6	258	0.9641	0.5938	0.9641	0.9819
No log	8.6667	260	0.9787	0.6101	0.9787	0.9893
No log	8.7333	262	1.0036	0.5979	1.0036	1.0018
No log	8.8	264	1.0227	0.5899	1.0227	1.0113
No log	8.8667	266	1.0195	0.5942	1.0195	1.0097
No log	8.9333	268	1.0168	0.5942	1.0168	1.0083
No log	9.0	270	1.0268	0.5856	1.0268	1.0133
No log	9.0667	272	1.0503	0.5864	1.0503	1.0248
No log	9.1333	274	1.0606	0.5864	1.0606	1.0299
No log	9.2	276	1.0627	0.5864	1.0627	1.0309
No log	9.2667	278	1.0659	0.5864	1.0659	1.0324
No log	9.3333	280	1.0646	0.5864	1.0646	1.0318
No log	9.4	282	1.0669	0.5864	1.0669	1.0329
No log	9.4667	284	1.0692	0.5864	1.0692	1.0340
No log	9.5333	286	1.0666	0.5864	1.0666	1.0328
No log	9.6	288	1.0580	0.5864	1.0580	1.0286
No log	9.6667	290	1.0515	0.5876	1.0515	1.0254
No log	9.7333	292	1.0475	0.5876	1.0475	1.0235
No log	9.8	294	1.0412	0.5876	1.0412	1.0204
No log	9.8667	296	1.0343	0.5856	1.0343	1.0170
No log	9.9333	298	1.0299	0.5856	1.0299	1.0149
No log	10.0	300	1.0284	0.5856	1.0284	1.0141

Framework versions

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