ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k4_task2_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: 1.1339
• Qwk: 0.4793
• Mse: 1.1339
• Rmse: 1.0648

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	0.08	2	4.2323	0.0024	4.2323	2.0573
No log	0.16	4	2.4624	0.0740	2.4624	1.5692
No log	0.24	6	1.3719	0.0696	1.3719	1.1713
No log	0.32	8	1.0912	0.0065	1.0912	1.0446
No log	0.4	10	0.8099	0.1097	0.8099	0.8999
No log	0.48	12	0.7546	0.1964	0.7546	0.8687
No log	0.56	14	0.7643	0.1873	0.7643	0.8742
No log	0.64	16	0.8167	0.2813	0.8167	0.9037
No log	0.72	18	0.7295	0.2433	0.7295	0.8541
No log	0.8	20	0.6713	0.2905	0.6713	0.8193
No log	0.88	22	0.6696	0.2806	0.6696	0.8183
No log	0.96	24	0.6239	0.2851	0.6239	0.7899
No log	1.04	26	0.6034	0.3407	0.6034	0.7768
No log	1.12	28	0.6094	0.3422	0.6094	0.7806
No log	1.2	30	0.5871	0.3826	0.5871	0.7662
No log	1.28	32	0.6002	0.3680	0.6002	0.7747
No log	1.3600	34	0.6021	0.3808	0.6021	0.7760
No log	1.44	36	0.6102	0.4254	0.6102	0.7812
No log	1.52	38	0.8851	0.3417	0.8851	0.9408
No log	1.6	40	1.0479	0.3639	1.0479	1.0237
No log	1.6800	42	0.7045	0.3686	0.7045	0.8394
No log	1.76	44	0.6550	0.5122	0.6550	0.8093
No log	1.8400	46	0.6656	0.5130	0.6656	0.8158
No log	1.92	48	0.6938	0.5577	0.6938	0.8329
No log	2.0	50	0.6669	0.5202	0.6669	0.8166
No log	2.08	52	0.6902	0.4531	0.6902	0.8308
No log	2.16	54	0.7726	0.4290	0.7726	0.8790
No log	2.24	56	0.8466	0.4445	0.8466	0.9201
No log	2.32	58	0.8047	0.4524	0.8047	0.8971
No log	2.4	60	0.7718	0.4847	0.7718	0.8785
No log	2.48	62	0.7519	0.4511	0.7519	0.8671
No log	2.56	64	0.7668	0.5186	0.7668	0.8757
No log	2.64	66	0.7758	0.5186	0.7758	0.8808
No log	2.7200	68	0.7368	0.4682	0.7368	0.8584
No log	2.8	70	0.8105	0.4500	0.8105	0.9003
No log	2.88	72	0.8247	0.4596	0.8247	0.9081
No log	2.96	74	0.7792	0.4637	0.7792	0.8827
No log	3.04	76	0.7986	0.5189	0.7986	0.8936
No log	3.12	78	0.8166	0.5294	0.8166	0.9037
No log	3.2	80	0.8477	0.5112	0.8477	0.9207
No log	3.2800	82	0.8523	0.4641	0.8523	0.9232
No log	3.36	84	0.9255	0.4524	0.9255	0.9621
No log	3.44	86	0.9396	0.4592	0.9396	0.9694
No log	3.52	88	0.9477	0.5183	0.9477	0.9735
No log	3.6	90	1.0187	0.4767	1.0187	1.0093
No log	3.68	92	1.0166	0.5050	1.0166	1.0083
No log	3.76	94	1.0070	0.4828	1.0070	1.0035
No log	3.84	96	1.0974	0.4704	1.0974	1.0476
No log	3.92	98	1.1460	0.4798	1.1460	1.0705
No log	4.0	100	1.0484	0.4674	1.0484	1.0239
No log	4.08	102	1.0111	0.4896	1.0111	1.0056
No log	4.16	104	1.0692	0.4615	1.0692	1.0340
No log	4.24	106	1.1015	0.4374	1.1015	1.0495
No log	4.32	108	1.0084	0.4802	1.0084	1.0042
No log	4.4	110	0.9521	0.4978	0.9521	0.9757
No log	4.48	112	1.1856	0.4487	1.1856	1.0889
No log	4.5600	114	1.3785	0.4338	1.3785	1.1741
No log	4.64	116	1.2631	0.4404	1.2631	1.1239
No log	4.72	118	1.0262	0.4912	1.0262	1.0130
No log	4.8	120	0.9692	0.5162	0.9692	0.9845
No log	4.88	122	1.0812	0.4766	1.0812	1.0398
No log	4.96	124	1.1654	0.4694	1.1654	1.0795
No log	5.04	126	1.1005	0.5045	1.1005	1.0491
No log	5.12	128	0.9691	0.5196	0.9691	0.9844
No log	5.2	130	1.0041	0.4728	1.0041	1.0021
No log	5.28	132	1.0810	0.4493	1.0810	1.0397
No log	5.36	134	1.1364	0.4923	1.1364	1.0660
No log	5.44	136	1.0908	0.4497	1.0908	1.0444
No log	5.52	138	1.0710	0.4748	1.0710	1.0349
No log	5.6	140	1.0767	0.5178	1.0767	1.0377
No log	5.68	142	1.1401	0.4974	1.1401	1.0678
No log	5.76	144	1.1957	0.4746	1.1957	1.0935
No log	5.84	146	1.1758	0.4900	1.1758	1.0844
No log	5.92	148	1.1258	0.5084	1.1258	1.0610
No log	6.0	150	1.0814	0.5091	1.0814	1.0399
No log	6.08	152	1.0710	0.4943	1.0710	1.0349
No log	6.16	154	1.0440	0.4607	1.0440	1.0217
No log	6.24	156	1.0218	0.4860	1.0218	1.0109
No log	6.32	158	1.0005	0.4854	1.0005	1.0002
No log	6.4	160	0.9835	0.4798	0.9835	0.9917
No log	6.48	162	0.9559	0.4814	0.9559	0.9777
No log	6.5600	164	0.9414	0.4782	0.9414	0.9702
No log	6.64	166	0.9295	0.4940	0.9295	0.9641
No log	6.72	168	0.9357	0.4935	0.9357	0.9673
No log	6.8	170	0.9659	0.4855	0.9659	0.9828
No log	6.88	172	0.9964	0.4847	0.9964	0.9982
No log	6.96	174	1.0482	0.4861	1.0482	1.0238
No log	7.04	176	1.0993	0.5037	1.0993	1.0485
No log	7.12	178	1.1322	0.5160	1.1322	1.0640
No log	7.2	180	1.1414	0.4836	1.1414	1.0684
No log	7.28	182	1.1473	0.4738	1.1473	1.0711
No log	7.36	184	1.1195	0.4890	1.1195	1.0581
No log	7.44	186	1.0726	0.4740	1.0726	1.0357
No log	7.52	188	1.0410	0.4760	1.0410	1.0203
No log	7.6	190	1.0321	0.4769	1.0321	1.0159
No log	7.68	192	1.0247	0.4829	1.0247	1.0123
No log	7.76	194	1.0297	0.4597	1.0297	1.0148
No log	7.84	196	1.0522	0.4811	1.0522	1.0258
No log	7.92	198	1.0549	0.4816	1.0549	1.0271
No log	8.0	200	1.0591	0.4549	1.0591	1.0291
No log	8.08	202	1.0750	0.5008	1.0750	1.0368
No log	8.16	204	1.0981	0.5048	1.0981	1.0479
No log	8.24	206	1.1129	0.5061	1.1129	1.0550
No log	8.32	208	1.1250	0.5061	1.1250	1.0606
No log	8.4	210	1.1334	0.4998	1.1334	1.0646
No log	8.48	212	1.1423	0.4686	1.1423	1.0688
No log	8.56	214	1.1519	0.4827	1.1519	1.0733
No log	8.64	216	1.1586	0.4680	1.1586	1.0764
No log	8.72	218	1.1594	0.4712	1.1594	1.0767
No log	8.8	220	1.1658	0.4601	1.1658	1.0797
No log	8.88	222	1.1737	0.4536	1.1737	1.0834
No log	8.96	224	1.1899	0.4763	1.1899	1.0908
No log	9.04	226	1.1942	0.4804	1.1942	1.0928
No log	9.12	228	1.1922	0.4804	1.1922	1.0919
No log	9.2	230	1.1874	0.4643	1.1874	1.0897
No log	9.28	232	1.1757	0.4586	1.1757	1.0843
No log	9.36	234	1.1632	0.4639	1.1632	1.0785
No log	9.44	236	1.1516	0.4566	1.1516	1.0731
No log	9.52	238	1.1424	0.4664	1.1424	1.0688
No log	9.6	240	1.1375	0.4625	1.1375	1.0665
No log	9.68	242	1.1354	0.4670	1.1354	1.0656
No log	9.76	244	1.1350	0.4842	1.1350	1.0654
No log	9.84	246	1.1345	0.4793	1.1345	1.0651
No log	9.92	248	1.1339	0.4793	1.1339	1.0649
No log	10.0	250	1.1339	0.4793	1.1339	1.0648

Framework versions

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