ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k6_task3_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: 0.6096
• Qwk: 0.4027
• Mse: 0.6096
• Rmse: 0.7807

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	0.0714	2	3.3307	0.0026	3.3307	1.8250
No log	0.1429	4	1.6942	-0.0070	1.6942	1.3016
No log	0.2143	6	0.8104	0.1169	0.8104	0.9002
No log	0.2857	8	0.6546	0.2749	0.6546	0.8091
No log	0.3571	10	0.5471	0.0638	0.5471	0.7396
No log	0.4286	12	0.5640	0.0569	0.5640	0.7510
No log	0.5	14	0.5255	0.0	0.5255	0.7249
No log	0.5714	16	0.5531	0.0	0.5531	0.7437
No log	0.6429	18	0.5623	0.0	0.5623	0.7499
No log	0.7143	20	0.5242	0.0569	0.5242	0.7240
No log	0.7857	22	0.5452	0.3333	0.5452	0.7383
No log	0.8571	24	0.6195	0.25	0.6195	0.7871
No log	0.9286	26	0.5119	0.2941	0.5119	0.7155
No log	1.0	28	0.6617	0.2000	0.6617	0.8135
No log	1.0714	30	0.8820	0.2000	0.8820	0.9391
No log	1.1429	32	0.8419	0.0210	0.8419	0.9175
No log	1.2143	34	0.7764	0.0720	0.7764	0.8811
No log	1.2857	36	0.6148	0.0	0.6148	0.7841
No log	1.3571	38	0.5197	0.0	0.5197	0.7209
No log	1.4286	40	0.5628	0.3475	0.5628	0.7502
No log	1.5	42	0.5615	0.3043	0.5615	0.7494
No log	1.5714	44	0.5103	0.0	0.5103	0.7143
No log	1.6429	46	0.5016	0.0	0.5016	0.7082
No log	1.7143	48	0.5838	0.0720	0.5838	0.7640
No log	1.7857	50	0.5221	0.1278	0.5221	0.7226
No log	1.8571	52	0.7221	0.2464	0.7221	0.8498
No log	1.9286	54	2.0530	0.0239	2.0530	1.4328
No log	2.0	56	2.1200	0.0649	2.1200	1.4560
No log	2.0714	58	1.1596	0.0929	1.1596	1.0768
No log	2.1429	60	0.7752	0.1644	0.7752	0.8805
No log	2.2143	62	0.4934	0.1429	0.4934	0.7024
No log	2.2857	64	0.5961	0.2533	0.5961	0.7721
No log	2.3571	66	0.6081	0.3032	0.6081	0.7798
No log	2.4286	68	0.5156	0.0986	0.5156	0.7180
No log	2.5	70	0.6162	0.2410	0.6162	0.7850
No log	2.5714	72	0.7869	0.2300	0.7869	0.8871
No log	2.6429	74	0.7139	0.1919	0.7139	0.8449
No log	2.7143	76	0.5540	0.2105	0.5540	0.7443
No log	2.7857	78	0.5760	0.2704	0.5760	0.7589
No log	2.8571	80	0.7008	0.2621	0.7008	0.8372
No log	2.9286	82	0.6113	0.3563	0.6113	0.7818
No log	3.0	84	0.5518	0.1141	0.5518	0.7429
No log	3.0714	86	0.7833	0.2676	0.7833	0.8850
No log	3.1429	88	0.7943	0.2579	0.7943	0.8912
No log	3.2143	90	0.5651	0.2444	0.5651	0.7517
No log	3.2857	92	0.5593	0.3295	0.5593	0.7478
No log	3.3571	94	0.5624	0.2444	0.5624	0.7499
No log	3.4286	96	0.5555	0.2688	0.5555	0.7453
No log	3.5	98	0.5363	0.3446	0.5363	0.7323
No log	3.5714	100	0.5019	0.3208	0.5019	0.7085
No log	3.6429	102	0.6091	0.2871	0.6091	0.7804
No log	3.7143	104	0.8252	0.1867	0.8252	0.9084
No log	3.7857	106	0.6380	0.4286	0.6380	0.7988
No log	3.8571	108	0.5760	0.3607	0.5760	0.7590
No log	3.9286	110	0.5952	0.3607	0.5952	0.7715
No log	4.0	112	0.6618	0.4338	0.6618	0.8135
No log	4.0714	114	0.8140	0.2253	0.8140	0.9022
No log	4.1429	116	0.8522	0.2253	0.8522	0.9232
No log	4.2143	118	0.5986	0.3769	0.5986	0.7737
No log	4.2857	120	0.6268	0.3702	0.6268	0.7917
No log	4.3571	122	0.5947	0.4396	0.5947	0.7712
No log	4.4286	124	0.5845	0.3874	0.5845	0.7645
No log	4.5	126	0.5912	0.4851	0.5912	0.7689
No log	4.5714	128	0.5715	0.4518	0.5715	0.7560
No log	4.6429	130	0.6758	0.3593	0.6758	0.8221
No log	4.7143	132	0.6735	0.3761	0.6735	0.8207
No log	4.7857	134	0.5932	0.4882	0.5932	0.7702
No log	4.8571	136	0.5830	0.4882	0.5830	0.7635
No log	4.9286	138	0.5617	0.5423	0.5617	0.7495
No log	5.0	140	0.5765	0.5074	0.5765	0.7593
No log	5.0714	142	0.7124	0.25	0.7124	0.8440
No log	5.1429	144	0.6397	0.4233	0.6397	0.7998
No log	5.2143	146	0.6054	0.5	0.6054	0.7781
No log	5.2857	148	0.7828	0.2441	0.7828	0.8847
No log	5.3571	150	0.8429	0.25	0.8429	0.9181
No log	5.4286	152	0.7466	0.3414	0.7466	0.8641
No log	5.5	154	0.6662	0.4386	0.6662	0.8162
No log	5.5714	156	0.5554	0.4545	0.5554	0.7453
No log	5.6429	158	0.6733	0.4237	0.6733	0.8205
No log	5.7143	160	0.7877	0.3588	0.7877	0.8875
No log	5.7857	162	0.7121	0.3548	0.7121	0.8439
No log	5.8571	164	0.8512	0.3030	0.8512	0.9226
No log	5.9286	166	1.0298	0.1888	1.0298	1.0148
No log	6.0	168	0.8456	0.3359	0.8456	0.9196
No log	6.0714	170	0.5614	0.4286	0.5614	0.7492
No log	6.1429	172	0.5457	0.4400	0.5457	0.7387
No log	6.2143	174	0.6683	0.4087	0.6683	0.8175
No log	6.2857	176	0.9301	0.1884	0.9301	0.9644
No log	6.3571	178	0.9002	0.1882	0.9002	0.9488
No log	6.4286	180	0.7472	0.3016	0.7472	0.8644
No log	6.5	182	0.5311	0.48	0.5311	0.7288
No log	6.5714	184	0.5115	0.4400	0.5115	0.7152
No log	6.6429	186	0.5228	0.4902	0.5228	0.7230
No log	6.7143	188	0.6335	0.3982	0.6335	0.7959
No log	6.7857	190	0.8339	0.2450	0.8339	0.9132
No log	6.8571	192	0.9182	0.1524	0.9182	0.9582
No log	6.9286	194	0.7520	0.3021	0.7520	0.8672
No log	7.0	196	0.5891	0.4234	0.5891	0.7675
No log	7.0714	198	0.5301	0.4627	0.5301	0.7281
No log	7.1429	200	0.5434	0.5122	0.5434	0.7372
No log	7.2143	202	0.5891	0.4286	0.5891	0.7675
No log	7.2857	204	0.6482	0.3982	0.6482	0.8051
No log	7.3571	206	0.5799	0.4783	0.5799	0.7615
No log	7.4286	208	0.5772	0.4717	0.5772	0.7597
No log	7.5	210	0.6071	0.3929	0.6071	0.7792
No log	7.5714	212	0.6384	0.3665	0.6384	0.7990
No log	7.6429	214	0.7085	0.3684	0.7085	0.8417
No log	7.7143	216	0.7060	0.3684	0.7060	0.8402
No log	7.7857	218	0.8186	0.2424	0.8186	0.9048
No log	7.8571	220	0.8129	0.2756	0.8129	0.9016
No log	7.9286	222	0.6706	0.4035	0.6706	0.8189
No log	8.0	224	0.5313	0.4233	0.5313	0.7289
No log	8.0714	226	0.5120	0.4732	0.5120	0.7155
No log	8.1429	228	0.5359	0.4233	0.5359	0.7320
No log	8.2143	230	0.5737	0.4338	0.5737	0.7574
No log	8.2857	232	0.6386	0.4027	0.6386	0.7991
No log	8.3571	234	0.6708	0.3982	0.6708	0.8190
No log	8.4286	236	0.6569	0.4027	0.6569	0.8105
No log	8.5	238	0.5732	0.4654	0.5732	0.7571
No log	8.5714	240	0.5299	0.4233	0.5299	0.7279
No log	8.6429	242	0.5042	0.5025	0.5042	0.7101
No log	8.7143	244	0.5045	0.4059	0.5045	0.7102
No log	8.7857	246	0.5065	0.4171	0.5065	0.7117
No log	8.8571	248	0.5078	0.5025	0.5078	0.7126
No log	8.9286	250	0.5262	0.5330	0.5262	0.7254
No log	9.0	252	0.5616	0.4340	0.5616	0.7494
No log	9.0714	254	0.6034	0.4185	0.6034	0.7768
No log	9.1429	256	0.6204	0.4027	0.6204	0.7877
No log	9.2143	258	0.6401	0.4027	0.6401	0.8001
No log	9.2857	260	0.6238	0.4027	0.6238	0.7898
No log	9.3571	262	0.6098	0.4027	0.6098	0.7809
No log	9.4286	264	0.6214	0.4027	0.6214	0.7883
No log	9.5	266	0.6216	0.4027	0.6216	0.7884
No log	9.5714	268	0.6282	0.4027	0.6282	0.7926
No log	9.6429	270	0.6183	0.4027	0.6183	0.7863
No log	9.7143	272	0.6001	0.4286	0.6001	0.7747
No log	9.7857	274	0.5944	0.4286	0.5944	0.7710
No log	9.8571	276	0.5986	0.4286	0.5986	0.7737
No log	9.9286	278	0.6052	0.4027	0.6052	0.7779
No log	10.0	280	0.6096	0.4027	0.6096	0.7807

Framework versions

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