ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run1_AugV5_k3_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: 1.0604
• Qwk: 0.5030
• Mse: 1.0604
• Rmse: 1.0297

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	3.8640	-0.0206	3.8640	1.9657
No log	0.2222	4	1.9120	0.0305	1.9120	1.3828
No log	0.3333	6	1.1713	0.0153	1.1713	1.0823
No log	0.4444	8	0.9106	-0.0781	0.9106	0.9543
No log	0.5556	10	0.7625	0.1647	0.7625	0.8732
No log	0.6667	12	0.8004	0.0505	0.8004	0.8946
No log	0.7778	14	0.8108	0.0556	0.8108	0.9005
No log	0.8889	16	0.7777	0.0274	0.7777	0.8819
No log	1.0	18	0.8511	0.0387	0.8511	0.9225
No log	1.1111	20	0.8164	0.1172	0.8164	0.9035
No log	1.2222	22	0.8359	-0.1056	0.8359	0.9143
No log	1.3333	24	0.8548	-0.1251	0.8548	0.9245
No log	1.4444	26	0.7892	0.0046	0.7892	0.8884
No log	1.5556	28	0.7396	0.1431	0.7396	0.8600
No log	1.6667	30	0.7381	0.1676	0.7381	0.8591
No log	1.7778	32	0.7198	0.1257	0.7198	0.8484
No log	1.8889	34	0.7055	0.2466	0.7055	0.8399
No log	2.0	36	0.6811	0.2019	0.6811	0.8253
No log	2.1111	38	0.6907	0.1511	0.6907	0.8311
No log	2.2222	40	0.7531	0.1465	0.7531	0.8678
No log	2.3333	42	0.7136	0.2095	0.7136	0.8447
No log	2.4444	44	0.6287	0.3487	0.6287	0.7929
No log	2.5556	46	0.6220	0.3611	0.6220	0.7887
No log	2.6667	48	0.6376	0.4495	0.6376	0.7985
No log	2.7778	50	0.7974	0.3713	0.7974	0.8930
No log	2.8889	52	0.9845	0.3528	0.9845	0.9922
No log	3.0	54	0.9460	0.3589	0.9460	0.9726
No log	3.1111	56	0.7375	0.4856	0.7375	0.8588
No log	3.2222	58	0.6421	0.5030	0.6421	0.8013
No log	3.3333	60	0.6932	0.4531	0.6932	0.8326
No log	3.4444	62	0.6944	0.4587	0.6944	0.8333
No log	3.5556	64	0.6594	0.5181	0.6594	0.8121
No log	3.6667	66	0.6914	0.5323	0.6914	0.8315
No log	3.7778	68	0.7644	0.5132	0.7644	0.8743
No log	3.8889	70	0.7625	0.5122	0.7625	0.8732
No log	4.0	72	0.7418	0.5295	0.7418	0.8613
No log	4.1111	74	0.8180	0.5005	0.8180	0.9044
No log	4.2222	76	0.8145	0.5243	0.8145	0.9025
No log	4.3333	78	0.8041	0.4691	0.8041	0.8967
No log	4.4444	80	0.8657	0.4533	0.8657	0.9304
No log	4.5556	82	0.8461	0.4428	0.8461	0.9198
No log	4.6667	84	0.7754	0.4912	0.7754	0.8806
No log	4.7778	86	0.7897	0.4547	0.7897	0.8886
No log	4.8889	88	0.8093	0.4623	0.8093	0.8996
No log	5.0	90	0.8288	0.4885	0.8288	0.9104
No log	5.1111	92	0.8914	0.4990	0.8914	0.9441
No log	5.2222	94	0.9435	0.4830	0.9435	0.9713
No log	5.3333	96	1.0049	0.4468	1.0049	1.0024
No log	5.4444	98	1.0594	0.4763	1.0594	1.0293
No log	5.5556	100	1.0765	0.4576	1.0765	1.0375
No log	5.6667	102	1.0979	0.4650	1.0979	1.0478
No log	5.7778	104	1.1486	0.5011	1.1486	1.0717
No log	5.8889	106	1.1053	0.4990	1.1053	1.0513
No log	6.0	108	1.0725	0.4669	1.0725	1.0356
No log	6.1111	110	1.0515	0.4741	1.0515	1.0254
No log	6.2222	112	1.0328	0.4608	1.0328	1.0163
No log	6.3333	114	1.0372	0.4652	1.0372	1.0184
No log	6.4444	116	0.9814	0.4673	0.9814	0.9906
No log	6.5556	118	0.9403	0.4949	0.9403	0.9697
No log	6.6667	120	0.9481	0.5033	0.9481	0.9737
No log	6.7778	122	0.9522	0.4944	0.9522	0.9758
No log	6.8889	124	0.9319	0.4868	0.9319	0.9654
No log	7.0	126	0.9479	0.5074	0.9479	0.9736
No log	7.1111	128	0.9845	0.4998	0.9845	0.9922
No log	7.2222	130	1.0134	0.4600	1.0134	1.0067
No log	7.3333	132	1.0318	0.4735	1.0318	1.0158
No log	7.4444	134	1.0313	0.4605	1.0313	1.0155
No log	7.5556	136	1.0353	0.4613	1.0353	1.0175
No log	7.6667	138	1.0032	0.4749	1.0032	1.0016
No log	7.7778	140	0.9958	0.4874	0.9958	0.9979
No log	7.8889	142	1.0043	0.4752	1.0043	1.0021
No log	8.0	144	1.0134	0.4639	1.0134	1.0067
No log	8.1111	146	1.0254	0.4662	1.0254	1.0126
No log	8.2222	148	1.0458	0.4667	1.0458	1.0227
No log	8.3333	150	1.0487	0.4667	1.0487	1.0241
No log	8.4444	152	1.0357	0.4687	1.0357	1.0177
No log	8.5556	154	1.0109	0.4658	1.0109	1.0054
No log	8.6667	156	0.9919	0.5256	0.9919	0.9960
No log	8.7778	158	0.9939	0.5225	0.9939	0.9969
No log	8.8889	160	1.0055	0.5017	1.0055	1.0027
No log	9.0	162	1.0178	0.4926	1.0178	1.0089
No log	9.1111	164	1.0229	0.5159	1.0229	1.0114
No log	9.2222	166	1.0286	0.5096	1.0286	1.0142
No log	9.3333	168	1.0304	0.5165	1.0304	1.0151
No log	9.4444	170	1.0360	0.5099	1.0360	1.0179
No log	9.5556	172	1.0426	0.5099	1.0426	1.0211
No log	9.6667	174	1.0507	0.5364	1.0507	1.0250
No log	9.7778	176	1.0571	0.5037	1.0571	1.0281
No log	9.8889	178	1.0593	0.5030	1.0593	1.0292
No log	10.0	180	1.0604	0.5030	1.0604	1.0297

Framework versions

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