ArabicNewSplits4_WithDuplicationsForScore5_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: 0.7930
• Qwk: 0.5134
• Mse: 0.7930
• Rmse: 0.8905

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	0.0526	2	4.1716	0.0024	4.1716	2.0425
No log	0.1053	4	2.2482	0.0475	2.2482	1.4994
No log	0.1579	6	1.2264	0.0602	1.2264	1.1074
No log	0.2105	8	0.9066	-0.0691	0.9066	0.9521
No log	0.2632	10	0.7459	0.1762	0.7459	0.8636
No log	0.3158	12	0.7248	0.1469	0.7248	0.8514
No log	0.3684	14	0.7810	0.0772	0.7810	0.8838
No log	0.4211	16	0.7837	0.0682	0.7837	0.8853
No log	0.4737	18	0.7382	0.0960	0.7382	0.8592
No log	0.5263	20	0.7352	0.2333	0.7352	0.8574
No log	0.5789	22	0.9203	0.0111	0.9203	0.9593
No log	0.6316	24	0.8786	0.0417	0.8786	0.9373
No log	0.6842	26	0.7331	0.2212	0.7331	0.8562
No log	0.7368	28	0.7103	0.2333	0.7103	0.8428
No log	0.7895	30	0.6758	0.2333	0.6758	0.8221
No log	0.8421	32	0.6701	0.2245	0.6701	0.8186
No log	0.8947	34	0.6715	0.2422	0.6715	0.8195
No log	0.9474	36	0.6818	0.2928	0.6818	0.8257
No log	1.0	38	0.7317	0.2781	0.7317	0.8554
No log	1.0526	40	0.6394	0.2786	0.6394	0.7996
No log	1.1053	42	0.6306	0.3289	0.6306	0.7941
No log	1.1579	44	0.6309	0.3536	0.6309	0.7943
No log	1.2105	46	0.6278	0.3805	0.6278	0.7923
No log	1.2632	48	0.6674	0.4364	0.6674	0.8169
No log	1.3158	50	0.6313	0.4840	0.6313	0.7946
No log	1.3684	52	0.6462	0.4830	0.6462	0.8039
No log	1.4211	54	0.7836	0.4284	0.7836	0.8852
No log	1.4737	56	0.8638	0.4062	0.8638	0.9294
No log	1.5263	58	0.7439	0.4997	0.7439	0.8625
No log	1.5789	60	0.7820	0.4135	0.7820	0.8843
No log	1.6316	62	0.7102	0.5130	0.7102	0.8427
No log	1.6842	64	1.1215	0.3352	1.1215	1.0590
No log	1.7368	66	1.3374	0.3222	1.3374	1.1565
No log	1.7895	68	0.9715	0.3477	0.9715	0.9857
No log	1.8421	70	0.7229	0.4864	0.7229	0.8502
No log	1.8947	72	0.6970	0.4710	0.6970	0.8349
No log	1.9474	74	0.7346	0.4511	0.7346	0.8571
No log	2.0	76	0.9844	0.4678	0.9844	0.9922
No log	2.0526	78	1.2308	0.3858	1.2308	1.1094
No log	2.1053	80	1.0083	0.4937	1.0083	1.0042
No log	2.1579	82	0.8996	0.5230	0.8996	0.9485
No log	2.2105	84	1.0501	0.4603	1.0501	1.0247
No log	2.2632	86	1.0044	0.5051	1.0044	1.0022
No log	2.3158	88	1.1176	0.4978	1.1176	1.0572
No log	2.3684	90	1.1630	0.4609	1.1630	1.0784
No log	2.4211	92	1.0513	0.4910	1.0513	1.0253
No log	2.4737	94	0.9932	0.4766	0.9932	0.9966
No log	2.5263	96	0.9056	0.4852	0.9056	0.9516
No log	2.5789	98	0.8329	0.5282	0.8329	0.9126
No log	2.6316	100	0.8209	0.4773	0.8209	0.9060
No log	2.6842	102	1.2168	0.4416	1.2168	1.1031
No log	2.7368	104	1.3366	0.4239	1.3366	1.1561
No log	2.7895	106	1.0170	0.4939	1.0170	1.0085
No log	2.8421	108	0.7951	0.5375	0.7951	0.8917
No log	2.8947	110	0.8107	0.5084	0.8107	0.9004
No log	2.9474	112	0.9421	0.4920	0.9421	0.9706
No log	3.0	114	0.9079	0.4892	0.9079	0.9528
No log	3.0526	116	0.9633	0.4937	0.9633	0.9815
No log	3.1053	118	1.0017	0.4600	1.0017	1.0008
No log	3.1579	120	1.1289	0.4601	1.1289	1.0625
No log	3.2105	122	1.3073	0.4553	1.3073	1.1434
No log	3.2632	124	1.3349	0.4424	1.3349	1.1554
No log	3.3158	126	1.1492	0.471	1.1492	1.0720
No log	3.3684	128	1.1008	0.4546	1.1008	1.0492
No log	3.4211	130	1.1081	0.4931	1.1081	1.0526
No log	3.4737	132	1.2092	0.4645	1.2092	1.0996
No log	3.5263	134	1.3379	0.4239	1.3379	1.1567
No log	3.5789	136	1.1480	0.4647	1.1480	1.0714
No log	3.6316	138	0.8027	0.4813	0.8027	0.8959
No log	3.6842	140	0.7290	0.4885	0.7290	0.8538
No log	3.7368	142	0.7321	0.4931	0.7321	0.8556
No log	3.7895	144	0.9041	0.4521	0.9041	0.9509
No log	3.8421	146	1.2075	0.4471	1.2075	1.0989
No log	3.8947	148	1.0938	0.4668	1.0938	1.0458
No log	3.9474	150	0.8411	0.4857	0.8411	0.9171
No log	4.0	152	0.9768	0.4810	0.9768	0.9883
No log	4.0526	154	1.1468	0.4375	1.1468	1.0709
No log	4.1053	156	1.0126	0.4981	1.0126	1.0063
No log	4.1579	158	0.8869	0.4361	0.8869	0.9417
No log	4.2105	160	1.1257	0.4930	1.1257	1.0610
No log	4.2632	162	1.1806	0.4907	1.1806	1.0865
No log	4.3158	164	0.9987	0.4838	0.9987	0.9994
No log	4.3684	166	0.8130	0.4671	0.8130	0.9017
No log	4.4211	168	0.7994	0.5089	0.7994	0.8941
No log	4.4737	170	0.7945	0.4466	0.7945	0.8914
No log	4.5263	172	0.8143	0.4873	0.8143	0.9024
No log	4.5789	174	0.7848	0.5422	0.7848	0.8859
No log	4.6316	176	0.6834	0.5133	0.6834	0.8267
No log	4.6842	178	0.6470	0.5199	0.6470	0.8044
No log	4.7368	180	0.6532	0.5205	0.6532	0.8082
No log	4.7895	182	0.6773	0.5036	0.6773	0.8230
No log	4.8421	184	0.7155	0.5313	0.7155	0.8459
No log	4.8947	186	0.8145	0.5198	0.8145	0.9025
No log	4.9474	188	0.8323	0.5310	0.8323	0.9123
No log	5.0	190	0.8362	0.4985	0.8362	0.9144
No log	5.0526	192	0.8113	0.4550	0.8113	0.9007
No log	5.1053	194	0.8427	0.4933	0.8427	0.9180
No log	5.1579	196	0.8513	0.4543	0.8513	0.9227
No log	5.2105	198	0.9045	0.4667	0.9045	0.9511
No log	5.2632	200	0.9639	0.4881	0.9639	0.9818
No log	5.3158	202	0.9469	0.4851	0.9469	0.9731
No log	5.3684	204	1.0089	0.4773	1.0089	1.0045
No log	5.4211	206	1.0550	0.5021	1.0550	1.0271
No log	5.4737	208	0.9807	0.5041	0.9807	0.9903
No log	5.5263	210	0.8902	0.4708	0.8902	0.9435
No log	5.5789	212	0.8720	0.4700	0.8720	0.9338
No log	5.6316	214	0.8700	0.4574	0.8700	0.9327
No log	5.6842	216	0.9115	0.4654	0.9115	0.9547
No log	5.7368	218	0.9054	0.4619	0.9054	0.9515
No log	5.7895	220	0.9404	0.4936	0.9404	0.9697
No log	5.8421	222	0.9530	0.5157	0.9530	0.9762
No log	5.8947	224	0.9172	0.5274	0.9172	0.9577
No log	5.9474	226	0.8764	0.5095	0.8764	0.9362
No log	6.0	228	0.8495	0.5030	0.8495	0.9217
No log	6.0526	230	0.8500	0.4846	0.8500	0.9220
No log	6.1053	232	0.8643	0.4806	0.8643	0.9297
No log	6.1579	234	0.8846	0.4859	0.8846	0.9406
No log	6.2105	236	0.8685	0.5057	0.8685	0.9319
No log	6.2632	238	0.8335	0.5186	0.8335	0.9130
No log	6.3158	240	0.8373	0.4998	0.8373	0.9150
No log	6.3684	242	0.8716	0.5054	0.8716	0.9336
No log	6.4211	244	0.8742	0.5276	0.8742	0.9350
No log	6.4737	246	0.8228	0.5223	0.8228	0.9071
No log	6.5263	248	0.7245	0.5291	0.7245	0.8512
No log	6.5789	250	0.6595	0.5746	0.6595	0.8121
No log	6.6316	252	0.6625	0.5626	0.6625	0.8139
No log	6.6842	254	0.6547	0.5743	0.6547	0.8091
No log	6.7368	256	0.6940	0.5532	0.6940	0.8331
No log	6.7895	258	0.8451	0.5152	0.8451	0.9193
No log	6.8421	260	1.0473	0.4929	1.0473	1.0234
No log	6.8947	262	1.0944	0.4876	1.0944	1.0461
No log	6.9474	264	0.9971	0.4918	0.9971	0.9985
No log	7.0	266	0.8735	0.5068	0.8735	0.9346
No log	7.0526	268	0.8442	0.5529	0.8442	0.9188
No log	7.1053	270	0.8411	0.5492	0.8411	0.9171
No log	7.1579	272	0.8524	0.5148	0.8524	0.9233
No log	7.2105	274	0.9087	0.4908	0.9087	0.9533
No log	7.2632	276	0.9657	0.5057	0.9657	0.9827
No log	7.3158	278	0.9368	0.5126	0.9368	0.9679
No log	7.3684	280	0.8623	0.5097	0.8623	0.9286
No log	7.4211	282	0.8143	0.4941	0.8143	0.9024
No log	7.4737	284	0.7682	0.5220	0.7682	0.8765
No log	7.5263	286	0.7404	0.5228	0.7404	0.8605
No log	7.5789	288	0.7356	0.5160	0.7356	0.8577
No log	7.6316	290	0.7557	0.5106	0.7557	0.8693
No log	7.6842	292	0.7692	0.5100	0.7692	0.8770
No log	7.7368	294	0.7462	0.5191	0.7462	0.8639
No log	7.7895	296	0.7142	0.5039	0.7142	0.8451
No log	7.8421	298	0.6988	0.5298	0.6988	0.8359
No log	7.8947	300	0.7015	0.5243	0.7015	0.8375
No log	7.9474	302	0.7144	0.5088	0.7144	0.8452
No log	8.0	304	0.7301	0.4929	0.7301	0.8545
No log	8.0526	306	0.7539	0.4907	0.7539	0.8683
No log	8.1053	308	0.7762	0.4970	0.7762	0.8810
No log	8.1579	310	0.8059	0.5005	0.8059	0.8977
No log	8.2105	312	0.8221	0.5038	0.8221	0.9067
No log	8.2632	314	0.8316	0.5090	0.8316	0.9119
No log	8.3158	316	0.8183	0.4964	0.8183	0.9046
No log	8.3684	318	0.7965	0.4958	0.7965	0.8925
No log	8.4211	320	0.7985	0.4958	0.7985	0.8936
No log	8.4737	322	0.7955	0.5098	0.7955	0.8919
No log	8.5263	324	0.7968	0.5022	0.7968	0.8926
No log	8.5789	326	0.8092	0.5104	0.8092	0.8995
No log	8.6316	328	0.8293	0.5023	0.8293	0.9106
No log	8.6842	330	0.8704	0.5036	0.8704	0.9329
No log	8.7368	332	0.8995	0.5274	0.8995	0.9484
No log	8.7895	334	0.8961	0.5211	0.8961	0.9466
No log	8.8421	336	0.8756	0.5361	0.8756	0.9357
No log	8.8947	338	0.8465	0.5333	0.8465	0.9201
No log	8.9474	340	0.8047	0.5044	0.8047	0.8970
No log	9.0	342	0.7738	0.4990	0.7738	0.8796
No log	9.0526	344	0.7565	0.5100	0.7565	0.8698
No log	9.1053	346	0.7460	0.5065	0.7460	0.8637
No log	9.1579	348	0.7466	0.5065	0.7466	0.8641
No log	9.2105	350	0.7490	0.5065	0.7490	0.8655
No log	9.2632	352	0.7494	0.5	0.7494	0.8657
No log	9.3158	354	0.7526	0.5087	0.7526	0.8675
No log	9.3684	356	0.7540	0.5072	0.7540	0.8683
No log	9.4211	358	0.7526	0.5186	0.7526	0.8675
No log	9.4737	360	0.7527	0.5186	0.7527	0.8676
No log	9.5263	362	0.7567	0.5284	0.7567	0.8699
No log	9.5789	364	0.7660	0.5091	0.7660	0.8752
No log	9.6316	366	0.7768	0.5070	0.7768	0.8814
No log	9.6842	368	0.7836	0.5061	0.7836	0.8852
No log	9.7368	370	0.7894	0.4971	0.7894	0.8885
No log	9.7895	372	0.7908	0.5023	0.7908	0.8893
No log	9.8421	374	0.7911	0.5023	0.7911	0.8895
No log	9.8947	376	0.7931	0.5134	0.7931	0.8906
No log	9.9474	378	0.7930	0.5134	0.7930	0.8905
No log	10.0	380	0.7930	0.5134	0.7930	0.8905

Framework versions

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