ArabicNewSplits6_FineTuningAraBERT_run3_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: 0.7785
• Qwk: 0.4553
• Mse: 0.7785
• Rmse: 0.8823

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	0.0556	2	4.0848	-0.0435	4.0848	2.0211
No log	0.1111	4	1.9981	0.0672	1.9981	1.4135
No log	0.1667	6	1.1433	0.0678	1.1433	1.0692
No log	0.2222	8	1.1069	0.0296	1.1069	1.0521
No log	0.2778	10	1.0542	0.0296	1.0542	1.0267
No log	0.3333	12	0.8090	0.0271	0.8090	0.8995
No log	0.3889	14	0.8412	0.0189	0.8412	0.9172
No log	0.4444	16	0.7702	0.1685	0.7702	0.8776
No log	0.5	18	0.7437	0.1118	0.7437	0.8624
No log	0.5556	20	0.7334	0.1585	0.7334	0.8564
No log	0.6111	22	0.6887	0.2455	0.6887	0.8299
No log	0.6667	24	0.6927	0.2367	0.6927	0.8323
No log	0.7222	26	0.8152	0.2172	0.8152	0.9029
No log	0.7778	28	1.0516	0.0919	1.0516	1.0255
No log	0.8333	30	1.1285	0.0902	1.1285	1.0623
No log	0.8889	32	0.9518	0.1154	0.9518	0.9756
No log	0.9444	34	0.8678	0.1295	0.8678	0.9316
No log	1.0	36	0.9063	0.1350	0.9063	0.9520
No log	1.0556	38	0.7136	0.3480	0.7136	0.8447
No log	1.1111	40	0.6103	0.3739	0.6103	0.7812
No log	1.1667	42	0.6086	0.3266	0.6086	0.7801
No log	1.2222	44	0.6412	0.3859	0.6412	0.8008
No log	1.2778	46	0.8440	0.2443	0.8440	0.9187
No log	1.3333	48	0.7495	0.3853	0.7495	0.8657
No log	1.3889	50	0.6457	0.3967	0.6457	0.8036
No log	1.4444	52	0.7437	0.4457	0.7437	0.8624
No log	1.5	54	0.9344	0.2901	0.9344	0.9667
No log	1.5556	56	1.2664	0.2290	1.2664	1.1253
No log	1.6111	58	1.1890	0.2333	1.1890	1.0904
No log	1.6667	60	0.8330	0.2656	0.8330	0.9127
No log	1.7222	62	0.6791	0.3834	0.6791	0.8240
No log	1.7778	64	0.5910	0.4314	0.5910	0.7688
No log	1.8333	66	0.5843	0.4108	0.5843	0.7644
No log	1.8889	68	0.5878	0.4139	0.5878	0.7667
No log	1.9444	70	0.6132	0.2904	0.6132	0.7831
No log	2.0	72	0.6733	0.3810	0.6733	0.8205
No log	2.0556	74	0.6776	0.3772	0.6776	0.8232
No log	2.1111	76	0.6109	0.4555	0.6109	0.7816
No log	2.1667	78	0.5796	0.4413	0.5796	0.7613
No log	2.2222	80	0.5812	0.5083	0.5812	0.7624
No log	2.2778	82	0.5898	0.5514	0.5898	0.7680
No log	2.3333	84	0.6887	0.4120	0.6887	0.8299
No log	2.3889	86	1.0360	0.3209	1.0360	1.0178
No log	2.4444	88	1.1606	0.3179	1.1606	1.0773
No log	2.5	90	0.9154	0.3593	0.9154	0.9568
No log	2.5556	92	0.7459	0.3991	0.7459	0.8637
No log	2.6111	94	0.7827	0.4198	0.7827	0.8847
No log	2.6667	96	0.7882	0.4142	0.7882	0.8878
No log	2.7222	98	0.7859	0.3992	0.7859	0.8865
No log	2.7778	100	1.0104	0.4022	1.0104	1.0052
No log	2.8333	102	1.1720	0.3338	1.1720	1.0826
No log	2.8889	104	1.0298	0.3628	1.0298	1.0148
No log	2.9444	106	0.7305	0.3581	0.7305	0.8547
No log	3.0	108	0.6603	0.5074	0.6603	0.8126
No log	3.0556	110	0.7067	0.4506	0.7067	0.8406
No log	3.1111	112	0.6822	0.4692	0.6822	0.8259
No log	3.1667	114	0.6476	0.4935	0.6476	0.8047
No log	3.2222	116	0.7028	0.4154	0.7028	0.8383
No log	3.2778	118	0.7333	0.4371	0.7333	0.8563
No log	3.3333	120	0.7063	0.4472	0.7063	0.8404
No log	3.3889	122	0.6990	0.4466	0.6990	0.8361
No log	3.4444	124	0.7068	0.4404	0.7068	0.8407
No log	3.5	126	0.7306	0.4286	0.7306	0.8548
No log	3.5556	128	0.7719	0.4020	0.7719	0.8786
No log	3.6111	130	0.9618	0.3679	0.9618	0.9807
No log	3.6667	132	0.9352	0.3771	0.9352	0.9671
No log	3.7222	134	0.7629	0.3923	0.7629	0.8734
No log	3.7778	136	0.7075	0.4670	0.7075	0.8411
No log	3.8333	138	0.7354	0.4457	0.7354	0.8576
No log	3.8889	140	0.8336	0.3986	0.8336	0.9130
No log	3.9444	142	0.7826	0.4145	0.7826	0.8847
No log	4.0	144	0.7419	0.4443	0.7419	0.8614
No log	4.0556	146	0.7193	0.4733	0.7193	0.8481
No log	4.1111	148	0.7125	0.4793	0.7125	0.8441
No log	4.1667	150	0.7035	0.4795	0.7035	0.8388
No log	4.2222	152	0.7647	0.4647	0.7647	0.8744
No log	4.2778	154	0.7440	0.4656	0.7440	0.8626
No log	4.3333	156	0.6751	0.4531	0.6751	0.8216
No log	4.3889	158	0.6471	0.4899	0.6471	0.8044
No log	4.4444	160	0.6532	0.5019	0.6532	0.8082
No log	4.5	162	0.6742	0.4524	0.6742	0.8211
No log	4.5556	164	0.7419	0.4389	0.7419	0.8613
No log	4.6111	166	0.7585	0.4250	0.7585	0.8709
No log	4.6667	168	0.7193	0.4547	0.7193	0.8481
No log	4.7222	170	0.7139	0.5006	0.7139	0.8449
No log	4.7778	172	0.7786	0.4994	0.7786	0.8824
No log	4.8333	174	0.7806	0.5011	0.7806	0.8835
No log	4.8889	176	0.7737	0.4467	0.7737	0.8796
No log	4.9444	178	0.8255	0.4946	0.8255	0.9085
No log	5.0	180	0.9495	0.4256	0.9495	0.9744
No log	5.0556	182	0.9371	0.4290	0.9371	0.9680
No log	5.1111	184	0.8297	0.4500	0.8297	0.9109
No log	5.1667	186	0.7995	0.4732	0.7995	0.8942
No log	5.2222	188	0.8103	0.4773	0.8103	0.9001
No log	5.2778	190	0.7667	0.4861	0.7667	0.8756
No log	5.3333	192	0.7192	0.4358	0.7192	0.8480
No log	5.3889	194	0.7224	0.4423	0.7224	0.8499
No log	5.4444	196	0.7092	0.4584	0.7092	0.8421
No log	5.5	198	0.7178	0.4426	0.7178	0.8472
No log	5.5556	200	0.7302	0.4560	0.7302	0.8545
No log	5.6111	202	0.7420	0.4540	0.7420	0.8614
No log	5.6667	204	0.7612	0.4619	0.7612	0.8725
No log	5.7222	206	0.7705	0.4619	0.7705	0.8778
No log	5.7778	208	0.7669	0.4694	0.7669	0.8758
No log	5.8333	210	0.7711	0.5113	0.7711	0.8781
No log	5.8889	212	0.7745	0.4905	0.7745	0.8801
No log	5.9444	214	0.7755	0.4961	0.7755	0.8806
No log	6.0	216	0.7854	0.4720	0.7854	0.8862
No log	6.0556	218	0.7973	0.4983	0.7973	0.8929
No log	6.1111	220	0.8163	0.4291	0.8163	0.9035
No log	6.1667	222	0.8267	0.4309	0.8267	0.9092
No log	6.2222	224	0.8181	0.4460	0.8181	0.9045
No log	6.2778	226	0.8195	0.4668	0.8195	0.9052
No log	6.3333	228	0.8190	0.4673	0.8190	0.9050
No log	6.3889	230	0.8050	0.4636	0.8050	0.8972
No log	6.4444	232	0.7934	0.4372	0.7934	0.8907
No log	6.5	234	0.7749	0.4374	0.7749	0.8803
No log	6.5556	236	0.7651	0.4673	0.7651	0.8747
No log	6.6111	238	0.7678	0.4692	0.7678	0.8762
No log	6.6667	240	0.7612	0.4692	0.7612	0.8725
No log	6.7222	242	0.7540	0.4822	0.7540	0.8683
No log	6.7778	244	0.7434	0.4822	0.7434	0.8622
No log	6.8333	246	0.7343	0.4785	0.7343	0.8569
No log	6.8889	248	0.7437	0.4692	0.7437	0.8624
No log	6.9444	250	0.7619	0.4880	0.7619	0.8728
No log	7.0	252	0.7672	0.4880	0.7672	0.8759
No log	7.0556	254	0.7687	0.4508	0.7687	0.8768
No log	7.1111	256	0.7650	0.4508	0.7650	0.8747
No log	7.1667	258	0.7503	0.4508	0.7503	0.8662
No log	7.2222	260	0.7323	0.4692	0.7323	0.8557
No log	7.2778	262	0.7272	0.4877	0.7272	0.8527
No log	7.3333	264	0.7373	0.4899	0.7373	0.8587
No log	7.3889	266	0.7460	0.4997	0.7460	0.8637
No log	7.4444	268	0.7591	0.4941	0.7591	0.8713
No log	7.5	270	0.7515	0.4926	0.7515	0.8669
No log	7.5556	272	0.7528	0.4669	0.7528	0.8676
No log	7.6111	274	0.7715	0.4710	0.7715	0.8783
No log	7.6667	276	0.7862	0.4468	0.7862	0.8867
No log	7.7222	278	0.7925	0.4524	0.7925	0.8902
No log	7.7778	280	0.8015	0.4468	0.8015	0.8953
No log	7.8333	282	0.8013	0.4546	0.8013	0.8951
No log	7.8889	284	0.7928	0.4546	0.7928	0.8904
No log	7.9444	286	0.7942	0.4416	0.7942	0.8912
No log	8.0	288	0.8017	0.4284	0.8017	0.8954
No log	8.0556	290	0.8048	0.4284	0.8048	0.8971
No log	8.1111	292	0.8079	0.4284	0.8079	0.8988
No log	8.1667	294	0.8048	0.4284	0.8048	0.8971
No log	8.2222	296	0.7926	0.4206	0.7926	0.8903
No log	8.2778	298	0.7781	0.4103	0.7781	0.8821
No log	8.3333	300	0.7734	0.4387	0.7734	0.8794
No log	8.3889	302	0.7670	0.4325	0.7670	0.8758
No log	8.4444	304	0.7592	0.4325	0.7592	0.8713
No log	8.5	306	0.7537	0.4181	0.7537	0.8681
No log	8.5556	308	0.7387	0.4592	0.7387	0.8595
No log	8.6111	310	0.7254	0.4820	0.7254	0.8517
No log	8.6667	312	0.7201	0.4440	0.7201	0.8486
No log	8.7222	314	0.7280	0.4500	0.7280	0.8532
No log	8.7778	316	0.7406	0.4676	0.7406	0.8606
No log	8.8333	318	0.7431	0.4809	0.7431	0.8620
No log	8.8889	320	0.7455	0.4681	0.7455	0.8634
No log	8.9444	322	0.7450	0.4500	0.7450	0.8631
No log	9.0	324	0.7472	0.4537	0.7472	0.8644
No log	9.0556	326	0.7535	0.4537	0.7535	0.8680
No log	9.1111	328	0.7581	0.4537	0.7581	0.8707
No log	9.1667	330	0.7655	0.4437	0.7655	0.8749
No log	9.2222	332	0.7718	0.4527	0.7718	0.8785
No log	9.2778	334	0.7759	0.4527	0.7759	0.8808
No log	9.3333	336	0.7782	0.4437	0.7782	0.8821
No log	9.3889	338	0.7788	0.4437	0.7788	0.8825
No log	9.4444	340	0.7784	0.4437	0.7784	0.8823
No log	9.5	342	0.7774	0.4492	0.7774	0.8817
No log	9.5556	344	0.7769	0.4684	0.7769	0.8814
No log	9.6111	346	0.7761	0.4684	0.7761	0.8810
No log	9.6667	348	0.7760	0.4684	0.7760	0.8809
No log	9.7222	350	0.7770	0.4684	0.7770	0.8815
No log	9.7778	352	0.7778	0.4553	0.7778	0.8819
No log	9.8333	354	0.7782	0.4553	0.7782	0.8821
No log	9.8889	356	0.7784	0.4684	0.7784	0.8822
No log	9.9444	358	0.7784	0.4553	0.7784	0.8823
No log	10.0	360	0.7785	0.4553	0.7785	0.8823

Framework versions

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