Arabic_FineTuningAraBERT_AugV5_k3_task3_organization_fold1

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: 0.6023
• Qwk: 0.1852
• Mse: 0.6023
• Rmse: 0.7761

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	0.1111	2	3.2691	0.0041	3.2691	1.8081
No log	0.2222	4	1.5440	-0.0168	1.5440	1.2426
No log	0.3333	6	1.0494	-0.4426	1.0494	1.0244
No log	0.4444	8	0.7627	0.0	0.7627	0.8733
No log	0.5556	10	0.7207	-0.0421	0.7207	0.8489
No log	0.6667	12	1.1277	-0.1000	1.1277	1.0619
No log	0.7778	14	0.7978	-0.2791	0.7978	0.8932
No log	0.8889	16	0.6799	0.0	0.6799	0.8246
No log	1.0	18	0.6912	0.0	0.6912	0.8314
No log	1.1111	20	0.7478	-0.0233	0.7478	0.8647
No log	1.2222	22	0.7894	-0.2692	0.7894	0.8885
No log	1.3333	24	0.8841	-0.1074	0.8841	0.9403
No log	1.4444	26	0.9616	0.1646	0.9616	0.9806
No log	1.5556	28	0.8752	0.0403	0.8752	0.9355
No log	1.6667	30	0.7599	-0.2655	0.7599	0.8717
No log	1.7778	32	0.8963	0.0571	0.8963	0.9467
No log	1.8889	34	1.2057	0.0	1.2057	1.0980
No log	2.0	36	1.1424	0.0	1.1424	1.0688
No log	2.1111	38	0.9274	0.0	0.9274	0.9630
No log	2.2222	40	0.6915	0.0	0.6915	0.8316
No log	2.3333	42	0.6934	-0.0577	0.6934	0.8327
No log	2.4444	44	1.0658	0.0120	1.0658	1.0324
No log	2.5556	46	2.2327	-0.0267	2.2327	1.4942
No log	2.6667	48	1.8881	0.0	1.8881	1.3741
No log	2.7778	50	1.3046	0.0	1.3046	1.1422
No log	2.8889	52	0.8297	0.1879	0.8297	0.9109
No log	3.0	54	0.6838	0.0	0.6838	0.8269
No log	3.1111	56	0.6598	0.0	0.6598	0.8123
No log	3.2222	58	0.6455	0.0	0.6455	0.8034
No log	3.3333	60	0.6495	0.0	0.6495	0.8059
No log	3.4444	62	0.6547	0.0	0.6547	0.8092
No log	3.5556	64	0.6983	0.0	0.6983	0.8357
No log	3.6667	66	0.8622	-0.1074	0.8622	0.9286
No log	3.7778	68	1.0773	0.0	1.0773	1.0379
No log	3.8889	70	1.0490	0.0	1.0490	1.0242
No log	4.0	72	1.0322	0.0	1.0322	1.0160
No log	4.1111	74	0.9420	0.0	0.9420	0.9706
No log	4.2222	76	0.8430	0.0571	0.8430	0.9181
No log	4.3333	78	0.7792	-0.0577	0.7792	0.8827
No log	4.4444	80	0.7126	-0.0233	0.7126	0.8441
No log	4.5556	82	0.6694	0.0	0.6694	0.8182
No log	4.6667	84	0.6598	0.0	0.6598	0.8123
No log	4.7778	86	0.6827	0.0	0.6827	0.8263
No log	4.8889	88	0.7243	0.1239	0.7243	0.8511
No log	5.0	90	0.7197	0.1239	0.7197	0.8484
No log	5.1111	92	0.7406	0.0984	0.7406	0.8606
No log	5.2222	94	0.7973	0.0984	0.7973	0.8929
No log	5.3333	96	0.7799	0.0984	0.7799	0.8831
No log	5.4444	98	0.7187	0.1239	0.7187	0.8478
No log	5.5556	100	0.6871	0.1239	0.6871	0.8289
No log	5.6667	102	0.6141	0.0	0.6141	0.7836
No log	5.7778	104	0.5736	0.0	0.5736	0.7574
No log	5.8889	106	0.5768	0.0	0.5768	0.7595
No log	6.0	108	0.5742	0.0	0.5742	0.7577
No log	6.1111	110	0.5836	0.0	0.5836	0.7640
No log	6.2222	112	0.5875	0.0	0.5875	0.7665
No log	6.3333	114	0.5939	0.0	0.5939	0.7706
No log	6.4444	116	0.6115	0.0	0.6115	0.7820
No log	6.5556	118	0.6120	0.0	0.6120	0.7823
No log	6.6667	120	0.6020	-0.0233	0.6020	0.7759
No log	6.7778	122	0.6050	0.1895	0.6050	0.7778
No log	6.8889	124	0.6034	-0.0233	0.6034	0.7768
No log	7.0	126	0.6037	-0.0233	0.6037	0.7770
No log	7.1111	128	0.6084	-0.0233	0.6084	0.7800
No log	7.2222	130	0.6394	0.0	0.6394	0.7996
No log	7.3333	132	0.6494	0.0	0.6494	0.8059
No log	7.4444	134	0.6215	-0.0233	0.6215	0.7884
No log	7.5556	136	0.6098	0.1895	0.6098	0.7809
No log	7.6667	138	0.6302	0.1538	0.6302	0.7939
No log	7.7778	140	0.6763	0.1239	0.6763	0.8224
No log	7.8889	142	0.6795	0.1239	0.6795	0.8243
No log	8.0	144	0.6233	0.1538	0.6233	0.7895
No log	8.1111	146	0.5968	0.1895	0.5968	0.7725
No log	8.2222	148	0.6159	0.0	0.6159	0.7848
No log	8.3333	150	0.6337	0.0	0.6337	0.7961
No log	8.4444	152	0.6319	0.0	0.6319	0.7949
No log	8.5556	154	0.6303	0.0	0.6303	0.7939
No log	8.6667	156	0.6209	0.0	0.6209	0.7880
No log	8.7778	158	0.6141	0.1852	0.6141	0.7837
No log	8.8889	160	0.6148	0.1852	0.6148	0.7841
No log	9.0	162	0.6149	0.1852	0.6149	0.7842
No log	9.1111	164	0.6135	0.1852	0.6135	0.7832
No log	9.2222	166	0.6099	0.1852	0.6099	0.7810
No log	9.3333	168	0.6068	0.1852	0.6068	0.7790
No log	9.4444	170	0.6060	0.1852	0.6060	0.7784
No log	9.5556	172	0.6050	0.1852	0.6050	0.7778
No log	9.6667	174	0.6033	0.1852	0.6033	0.7767
No log	9.7778	176	0.6029	0.1852	0.6029	0.7765
No log	9.8889	178	0.6023	0.1852	0.6023	0.7761
No log	10.0	180	0.6023	0.1852	0.6023	0.7761

Framework versions

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