ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k8_task5_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: 1.1986
• Qwk: 0.5909
• Mse: 1.1986
• Rmse: 1.0948

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	2.4144	-0.0350	2.4144	1.5538
No log	0.1429	4	1.6143	0.0760	1.6143	1.2706
No log	0.2143	6	1.5262	0.1172	1.5262	1.2354
No log	0.2857	8	1.4181	0.2585	1.4181	1.1909
No log	0.3571	10	1.5937	0.2998	1.5937	1.2624
No log	0.4286	12	2.0439	0.2339	2.0439	1.4297
No log	0.5	14	1.9472	0.1355	1.9472	1.3954
No log	0.5714	16	1.8158	0.2905	1.8158	1.3475
No log	0.6429	18	1.6146	0.3350	1.6146	1.2707
No log	0.7143	20	1.4844	0.3599	1.4844	1.2184
No log	0.7857	22	1.4286	0.3576	1.4286	1.1952
No log	0.8571	24	1.4535	0.3967	1.4535	1.2056
No log	0.9286	26	1.4781	0.3968	1.4781	1.2158
No log	1.0	28	1.6605	0.3670	1.6605	1.2886
No log	1.0714	30	1.9520	0.3424	1.9520	1.3971
No log	1.1429	32	2.1558	0.2557	2.1558	1.4683
No log	1.2143	34	2.0933	0.2268	2.0933	1.4468
No log	1.2857	36	1.9270	0.1936	1.9270	1.3882
No log	1.3571	38	1.7828	0.2439	1.7828	1.3352
No log	1.4286	40	1.7126	0.3001	1.7126	1.3087
No log	1.5	42	1.6923	0.3811	1.6923	1.3009
No log	1.5714	44	1.6446	0.3701	1.6446	1.2824
No log	1.6429	46	1.6751	0.3778	1.6751	1.2943
No log	1.7143	48	1.6044	0.4074	1.6044	1.2666
No log	1.7857	50	1.6828	0.3511	1.6828	1.2972
No log	1.8571	52	1.7433	0.3285	1.7433	1.3203
No log	1.9286	54	1.7678	0.3625	1.7678	1.3296
No log	2.0	56	1.7213	0.3875	1.7213	1.3120
No log	2.0714	58	1.6606	0.3874	1.6606	1.2886
No log	2.1429	60	1.6907	0.3934	1.6907	1.3003
No log	2.2143	62	1.7492	0.3804	1.7492	1.3226
No log	2.2857	64	1.7602	0.3863	1.7602	1.3267
No log	2.3571	66	1.7281	0.3816	1.7281	1.3146
No log	2.4286	68	1.7211	0.4181	1.7211	1.3119
No log	2.5	70	1.7148	0.4263	1.7148	1.3095
No log	2.5714	72	1.8587	0.4395	1.8587	1.3633
No log	2.6429	74	1.9887	0.4328	1.9887	1.4102
No log	2.7143	76	2.1046	0.4191	2.1046	1.4507
No log	2.7857	78	1.8530	0.4367	1.8530	1.3612
No log	2.8571	80	1.5199	0.4732	1.5199	1.2328
No log	2.9286	82	1.4150	0.5329	1.4150	1.1895
No log	3.0	84	1.4803	0.5391	1.4803	1.2167
No log	3.0714	86	1.4862	0.5636	1.4862	1.2191
No log	3.1429	88	1.5934	0.5179	1.5934	1.2623
No log	3.2143	90	1.5575	0.5371	1.5575	1.2480
No log	3.2857	92	1.3749	0.5615	1.3749	1.1726
No log	3.3571	94	1.2188	0.5865	1.2188	1.1040
No log	3.4286	96	1.1231	0.6279	1.1231	1.0598
No log	3.5	98	1.0690	0.6308	1.0690	1.0339
No log	3.5714	100	1.0025	0.6606	1.0025	1.0013
No log	3.6429	102	1.0362	0.6490	1.0362	1.0180
No log	3.7143	104	1.2358	0.6298	1.2358	1.1117
No log	3.7857	106	1.5398	0.5591	1.5398	1.2409
No log	3.8571	108	1.6313	0.5376	1.6313	1.2772
No log	3.9286	110	1.7240	0.4768	1.7240	1.3130
No log	4.0	112	1.8626	0.4425	1.8626	1.3648
No log	4.0714	114	2.0248	0.4442	2.0248	1.4230
No log	4.1429	116	2.2227	0.4407	2.2227	1.4909
No log	4.2143	118	2.0574	0.4760	2.0574	1.4344
No log	4.2857	120	1.6506	0.5019	1.6506	1.2847
No log	4.3571	122	1.3131	0.5756	1.3131	1.1459
No log	4.4286	124	1.1154	0.6022	1.1154	1.0561
No log	4.5	126	1.1020	0.5933	1.1020	1.0498
No log	4.5714	128	1.1299	0.6174	1.1299	1.0630
No log	4.6429	130	1.2416	0.6032	1.2416	1.1143
No log	4.7143	132	1.2165	0.6059	1.2165	1.1029
No log	4.7857	134	1.1986	0.6221	1.1986	1.0948
No log	4.8571	136	1.1705	0.6176	1.1705	1.0819
No log	4.9286	138	1.0769	0.6430	1.0769	1.0377
No log	5.0	140	1.0208	0.6469	1.0208	1.0103
No log	5.0714	142	0.9916	0.6484	0.9916	0.9958
No log	5.1429	144	1.0286	0.6395	1.0286	1.0142
No log	5.2143	146	1.2556	0.6224	1.2556	1.1205
No log	5.2857	148	1.4408	0.5918	1.4408	1.2003
No log	5.3571	150	1.3794	0.5880	1.3794	1.1745
No log	5.4286	152	1.2571	0.5920	1.2571	1.1212
No log	5.5	154	1.2289	0.5870	1.2289	1.1086
No log	5.5714	156	1.1360	0.6082	1.1360	1.0658
No log	5.6429	158	1.1240	0.6121	1.1240	1.0602
No log	5.7143	160	1.2120	0.5956	1.2120	1.1009
No log	5.7857	162	1.2542	0.5765	1.2542	1.1199
No log	5.8571	164	1.1573	0.5926	1.1573	1.0758
No log	5.9286	166	1.0488	0.6348	1.0488	1.0241
No log	6.0	168	0.9719	0.5830	0.9719	0.9858
No log	6.0714	170	1.0442	0.6154	1.0442	1.0218
No log	6.1429	172	1.1671	0.6024	1.1671	1.0803
No log	6.2143	174	1.2561	0.5906	1.2561	1.1208
No log	6.2857	176	1.2112	0.6015	1.2112	1.1005
No log	6.3571	178	1.1208	0.6102	1.1208	1.0587
No log	6.4286	180	1.1035	0.6232	1.1035	1.0505
No log	6.5	182	1.1438	0.6152	1.1438	1.0695
No log	6.5714	184	1.2169	0.6193	1.2169	1.1031
No log	6.6429	186	1.2167	0.6193	1.2167	1.1030
No log	6.7143	188	1.1596	0.6193	1.1596	1.0769
No log	6.7857	190	1.0984	0.6218	1.0984	1.0481
No log	6.8571	192	1.0248	0.6218	1.0248	1.0123
No log	6.9286	194	1.0256	0.6373	1.0256	1.0127
No log	7.0	196	1.0632	0.6218	1.0632	1.0311
No log	7.0714	198	1.1013	0.6104	1.1013	1.0494
No log	7.1429	200	1.0784	0.6097	1.0784	1.0384
No log	7.2143	202	1.0558	0.6155	1.0558	1.0275
No log	7.2857	204	0.9846	0.5974	0.9846	0.9923
No log	7.3571	206	0.9585	0.6078	0.9585	0.9790
No log	7.4286	208	0.9781	0.6086	0.9781	0.9890
No log	7.5	210	1.0191	0.6164	1.0191	1.0095
No log	7.5714	212	1.0388	0.6164	1.0388	1.0192
No log	7.6429	214	1.0348	0.6016	1.0348	1.0172
No log	7.7143	216	1.0475	0.6007	1.0475	1.0235
No log	7.7857	218	1.0381	0.6001	1.0381	1.0189
No log	7.8571	220	0.9980	0.5872	0.9980	0.9990
No log	7.9286	222	0.9531	0.5984	0.9531	0.9763
No log	8.0	224	0.9294	0.5841	0.9294	0.9641
No log	8.0714	226	0.9533	0.6018	0.9533	0.9764
No log	8.1429	228	0.9860	0.5885	0.9860	0.9930
No log	8.2143	230	1.0127	0.5865	1.0127	1.0063
No log	8.2857	232	1.0610	0.5933	1.0610	1.0300
No log	8.3571	234	1.0980	0.5917	1.0980	1.0478
No log	8.4286	236	1.1164	0.5917	1.1164	1.0566
No log	8.5	238	1.1381	0.5994	1.1381	1.0668
No log	8.5714	240	1.1253	0.5977	1.1253	1.0608
No log	8.6429	242	1.1005	0.5959	1.1005	1.0490
No log	8.7143	244	1.0740	0.5818	1.0740	1.0364
No log	8.7857	246	1.0854	0.5869	1.0854	1.0418
No log	8.8571	248	1.0939	0.5869	1.0939	1.0459
No log	8.9286	250	1.1173	0.5977	1.1173	1.0570
No log	9.0	252	1.1476	0.5994	1.1476	1.0713
No log	9.0714	254	1.1652	0.5999	1.1652	1.0794
No log	9.1429	256	1.1707	0.5920	1.1707	1.0820
No log	9.2143	258	1.1688	0.5920	1.1688	1.0811
No log	9.2857	260	1.1671	0.5920	1.1671	1.0803
No log	9.3571	262	1.1759	0.5920	1.1759	1.0844
No log	9.4286	264	1.1717	0.5920	1.1717	1.0825
No log	9.5	266	1.1690	0.5920	1.1690	1.0812
No log	9.5714	268	1.1711	0.5920	1.1711	1.0822
No log	9.6429	270	1.1760	0.5920	1.1760	1.0844
No log	9.7143	272	1.1827	0.5909	1.1827	1.0875
No log	9.7857	274	1.1892	0.5909	1.1892	1.0905
No log	9.8571	276	1.1941	0.5909	1.1941	1.0928
No log	9.9286	278	1.1975	0.5909	1.1975	1.0943
No log	10.0	280	1.1986	0.5909	1.1986	1.0948

Framework versions

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