ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k7_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: 0.7835
• Qwk: 0.4917
• Mse: 0.7835
• Rmse: 0.8851

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	0.0556	2	4.0350	-0.0151	4.0350	2.0087
No log	0.1111	4	2.3475	0.0014	2.3475	1.5321
No log	0.1667	6	1.2845	0.0163	1.2845	1.1334
No log	0.2222	8	0.9203	-0.1031	0.9203	0.9593
No log	0.2778	10	0.8356	0.0328	0.8356	0.9141
No log	0.3333	12	0.8014	0.1249	0.8014	0.8952
No log	0.3889	14	0.7644	0.2015	0.7644	0.8743
No log	0.4444	16	0.7335	0.1874	0.7335	0.8565
No log	0.5	18	0.7015	0.1623	0.7015	0.8376
No log	0.5556	20	0.7164	0.2086	0.7164	0.8464
No log	0.6111	22	0.7009	0.2125	0.7009	0.8372
No log	0.6667	24	0.6493	0.3267	0.6493	0.8058
No log	0.7222	26	0.6114	0.3229	0.6114	0.7819
No log	0.7778	28	0.5959	0.3968	0.5959	0.7719
No log	0.8333	30	0.6969	0.3722	0.6969	0.8348
No log	0.8889	32	0.6472	0.4422	0.6472	0.8045
No log	0.9444	34	0.6323	0.4287	0.6323	0.7952
No log	1.0	36	0.6150	0.4501	0.6150	0.7842
No log	1.0556	38	0.6460	0.3956	0.6460	0.8037
No log	1.1111	40	0.6386	0.4429	0.6386	0.7991
No log	1.1667	42	0.7271	0.4032	0.7271	0.8527
No log	1.2222	44	1.0615	0.3186	1.0615	1.0303
No log	1.2778	46	0.9280	0.3333	0.9280	0.9633
No log	1.3333	48	0.5967	0.4001	0.5967	0.7724
No log	1.3889	50	0.5518	0.4068	0.5518	0.7428
No log	1.4444	52	0.5874	0.4095	0.5874	0.7664
No log	1.5	54	0.6261	0.3787	0.6261	0.7913
No log	1.5556	56	0.5503	0.4448	0.5503	0.7418
No log	1.6111	58	0.5841	0.4079	0.5841	0.7642
No log	1.6667	60	0.7695	0.4451	0.7695	0.8772
No log	1.7222	62	0.7037	0.4587	0.7037	0.8389
No log	1.7778	64	0.6133	0.4420	0.6133	0.7832
No log	1.8333	66	0.6432	0.4769	0.6432	0.8020
No log	1.8889	68	0.6609	0.5066	0.6609	0.8129
No log	1.9444	70	0.7171	0.4537	0.7171	0.8468
No log	2.0	72	0.7298	0.4844	0.7298	0.8543
No log	2.0556	74	0.7297	0.4965	0.7297	0.8542
No log	2.1111	76	0.7370	0.5006	0.7370	0.8585
No log	2.1667	78	0.7932	0.4574	0.7932	0.8906
No log	2.2222	80	0.7744	0.4636	0.7744	0.8800
No log	2.2778	82	0.7583	0.4809	0.7583	0.8708
No log	2.3333	84	0.7176	0.4797	0.7176	0.8471
No log	2.3889	86	0.7468	0.5020	0.7468	0.8642
No log	2.4444	88	0.7317	0.5172	0.7317	0.8554
No log	2.5	90	0.6939	0.5170	0.6939	0.8330
No log	2.5556	92	0.7624	0.4635	0.7624	0.8731
No log	2.6111	94	1.3602	0.3324	1.3602	1.1663
No log	2.6667	96	1.7830	0.1624	1.7830	1.3353
No log	2.7222	98	1.6292	0.1818	1.6292	1.2764
No log	2.7778	100	1.1544	0.3174	1.1544	1.0745
No log	2.8333	102	0.7843	0.3708	0.7843	0.8856
No log	2.8889	104	0.6379	0.4287	0.6379	0.7987
No log	2.9444	106	0.6191	0.4787	0.6191	0.7868
No log	3.0	108	0.6204	0.4520	0.6204	0.7877
No log	3.0556	110	0.6419	0.4951	0.6419	0.8012
No log	3.1111	112	0.6764	0.4619	0.6764	0.8225
No log	3.1667	114	0.6823	0.4813	0.6823	0.8260
No log	3.2222	116	0.7158	0.4555	0.7158	0.8461
No log	3.2778	118	0.7857	0.4465	0.7857	0.8864
No log	3.3333	120	0.7880	0.4510	0.7880	0.8877
No log	3.3889	122	0.7554	0.4220	0.7554	0.8691
No log	3.4444	124	0.7666	0.4527	0.7666	0.8755
No log	3.5	126	0.7805	0.4499	0.7805	0.8834
No log	3.5556	128	0.8018	0.4459	0.8018	0.8954
No log	3.6111	130	0.8423	0.4806	0.8423	0.9178
No log	3.6667	132	0.8267	0.4856	0.8267	0.9092
No log	3.7222	134	0.8709	0.4737	0.8709	0.9332
No log	3.7778	136	0.8672	0.4560	0.8672	0.9312
No log	3.8333	138	0.8742	0.5031	0.8742	0.9350
No log	3.8889	140	0.8908	0.5152	0.8908	0.9438
No log	3.9444	142	0.8970	0.5072	0.8970	0.9471
No log	4.0	144	0.8886	0.5008	0.8886	0.9426
No log	4.0556	146	0.7838	0.4752	0.7838	0.8853
No log	4.1111	148	0.7310	0.5003	0.7310	0.8550
No log	4.1667	150	0.7401	0.5194	0.7401	0.8603
No log	4.2222	152	0.7041	0.5100	0.7041	0.8391
No log	4.2778	154	0.6995	0.4836	0.6995	0.8364
No log	4.3333	156	0.7802	0.4153	0.7802	0.8833
No log	4.3889	158	0.8310	0.4235	0.8310	0.9116
No log	4.4444	160	0.7253	0.4435	0.7253	0.8516
No log	4.5	162	0.6480	0.4801	0.6480	0.8050
No log	4.5556	164	0.7049	0.5542	0.7049	0.8396
No log	4.6111	166	0.7407	0.4782	0.7407	0.8607
No log	4.6667	168	0.6939	0.5590	0.6939	0.8330
No log	4.7222	170	0.6976	0.4870	0.6976	0.8352
No log	4.7778	172	0.7132	0.4627	0.7132	0.8445
No log	4.8333	174	0.7387	0.4623	0.7387	0.8595
No log	4.8889	176	0.7768	0.4874	0.7768	0.8813
No log	4.9444	178	0.8089	0.4683	0.8089	0.8994
No log	5.0	180	0.9014	0.4068	0.9014	0.9494
No log	5.0556	182	0.9536	0.4319	0.9536	0.9765
No log	5.1111	184	0.8928	0.4247	0.8928	0.9449
No log	5.1667	186	0.8597	0.4756	0.8597	0.9272
No log	5.2222	188	0.8821	0.5140	0.8821	0.9392
No log	5.2778	190	0.8394	0.5011	0.8394	0.9162
No log	5.3333	192	0.7822	0.4438	0.7822	0.8844
No log	5.3889	194	0.7929	0.4726	0.7929	0.8905
No log	5.4444	196	0.8012	0.4823	0.8012	0.8951
No log	5.5	198	0.7638	0.4903	0.7638	0.8740
No log	5.5556	200	0.7607	0.4796	0.7607	0.8722
No log	5.6111	202	0.7712	0.4980	0.7712	0.8782
No log	5.6667	204	0.7697	0.4964	0.7697	0.8773
No log	5.7222	206	0.7739	0.5076	0.7739	0.8797
No log	5.7778	208	0.7923	0.4698	0.7923	0.8901
No log	5.8333	210	0.8063	0.4661	0.8063	0.8980
No log	5.8889	212	0.8188	0.4661	0.8188	0.9049
No log	5.9444	214	0.8102	0.4693	0.8102	0.9001
No log	6.0	216	0.8375	0.4742	0.8375	0.9152
No log	6.0556	218	0.8845	0.4976	0.8845	0.9405
No log	6.1111	220	0.9102	0.4715	0.9102	0.9540
No log	6.1667	222	0.9085	0.4794	0.9085	0.9531
No log	6.2222	224	0.8567	0.4742	0.8567	0.9256
No log	6.2778	226	0.8237	0.4866	0.8237	0.9076
No log	6.3333	228	0.8307	0.5159	0.8307	0.9114
No log	6.3889	230	0.8018	0.5153	0.8018	0.8955
No log	6.4444	232	0.7360	0.4689	0.7360	0.8579
No log	6.5	234	0.7140	0.4785	0.7140	0.8450
No log	6.5556	236	0.7412	0.4799	0.7412	0.8609
No log	6.6111	238	0.7443	0.4813	0.7443	0.8627
No log	6.6667	240	0.7484	0.4986	0.7484	0.8651
No log	6.7222	242	0.7990	0.5014	0.7990	0.8939
No log	6.7778	244	0.8337	0.4913	0.8337	0.9130
No log	6.8333	246	0.8266	0.5030	0.8266	0.9092
No log	6.8889	248	0.8168	0.4933	0.8168	0.9038
No log	6.9444	250	0.8223	0.4765	0.8223	0.9068
No log	7.0	252	0.8179	0.4892	0.8179	0.9044
No log	7.0556	254	0.8032	0.4676	0.8032	0.8962
No log	7.1111	256	0.7899	0.4626	0.7899	0.8888
No log	7.1667	258	0.7685	0.4554	0.7685	0.8767
No log	7.2222	260	0.7425	0.4954	0.7425	0.8617
No log	7.2778	262	0.7360	0.4954	0.7360	0.8579
No log	7.3333	264	0.7272	0.4530	0.7272	0.8528
No log	7.3889	266	0.7460	0.4564	0.7460	0.8637
No log	7.4444	268	0.7509	0.4722	0.7509	0.8666
No log	7.5	270	0.7234	0.4575	0.7234	0.8506
No log	7.5556	272	0.6938	0.4832	0.6938	0.8330
No log	7.6111	274	0.6975	0.5087	0.6975	0.8352
No log	7.6667	276	0.7235	0.5235	0.7235	0.8506
No log	7.7222	278	0.7417	0.4956	0.7417	0.8612
No log	7.7778	280	0.7637	0.5083	0.7637	0.8739
No log	7.8333	282	0.7845	0.4873	0.7845	0.8857
No log	7.8889	284	0.8263	0.4533	0.8263	0.9090
No log	7.9444	286	0.8724	0.4500	0.8724	0.9340
No log	8.0	288	0.8817	0.4465	0.8817	0.9390
No log	8.0556	290	0.8512	0.4498	0.8512	0.9226
No log	8.1111	292	0.8153	0.4653	0.8153	0.9029
No log	8.1667	294	0.7908	0.4463	0.7908	0.8893
No log	8.2222	296	0.7803	0.4662	0.7803	0.8834
No log	8.2778	298	0.7753	0.4829	0.7753	0.8805
No log	8.3333	300	0.7630	0.4644	0.7630	0.8735
No log	8.3889	302	0.7537	0.4644	0.7537	0.8681
No log	8.4444	304	0.7405	0.4809	0.7405	0.8605
No log	8.5	306	0.7329	0.4580	0.7329	0.8561
No log	8.5556	308	0.7333	0.4697	0.7333	0.8563
No log	8.6111	310	0.7372	0.4697	0.7372	0.8586
No log	8.6667	312	0.7390	0.4613	0.7390	0.8596
No log	8.7222	314	0.7436	0.4392	0.7436	0.8623
No log	8.7778	316	0.7416	0.4316	0.7416	0.8612
No log	8.8333	318	0.7429	0.4558	0.7429	0.8619
No log	8.8889	320	0.7475	0.4834	0.7475	0.8646
No log	8.9444	322	0.7538	0.4572	0.7538	0.8682
No log	9.0	324	0.7586	0.4572	0.7586	0.8710
No log	9.0556	326	0.7574	0.4627	0.7574	0.8703
No log	9.1111	328	0.7560	0.4572	0.7560	0.8695
No log	9.1667	330	0.7576	0.4645	0.7576	0.8704
No log	9.2222	332	0.7584	0.4645	0.7584	0.8709
No log	9.2778	334	0.7602	0.4645	0.7602	0.8719
No log	9.3333	336	0.7630	0.4572	0.7630	0.8735
No log	9.3889	338	0.7662	0.4627	0.7662	0.8753
No log	9.4444	340	0.7692	0.4627	0.7692	0.8770
No log	9.5	342	0.7735	0.4627	0.7735	0.8795
No log	9.5556	344	0.7765	0.4627	0.7765	0.8812
No log	9.6111	346	0.7782	0.4572	0.7782	0.8822
No log	9.6667	348	0.7806	0.4572	0.7806	0.8835
No log	9.7222	350	0.7819	0.4587	0.7819	0.8843
No log	9.7778	352	0.7823	0.4658	0.7823	0.8845
No log	9.8333	354	0.7828	0.4658	0.7828	0.8848
No log	9.8889	356	0.7834	0.4917	0.7834	0.8851
No log	9.9444	358	0.7835	0.4917	0.7835	0.8852
No log	10.0	360	0.7835	0.4917	0.7835	0.8851

Framework versions

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