ArabicNewSplits7_FineTuningAraBERT_noAug_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: 0.8484
• Qwk: 0.4924
• Mse: 0.8484
• Rmse: 0.9211

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.6667	2	4.0443	0.0069	4.0443	2.0110
No log	1.3333	4	2.5276	0.0248	2.5276	1.5899
No log	2.0	6	1.4136	0.0513	1.4136	1.1889
No log	2.6667	8	1.0688	0.1962	1.0688	1.0338
No log	3.3333	10	1.0567	0.1516	1.0567	1.0279
No log	4.0	12	1.0572	0.0864	1.0572	1.0282
No log	4.6667	14	1.0428	0.2024	1.0428	1.0212
No log	5.3333	16	0.9712	0.2618	0.9712	0.9855
No log	6.0	18	0.8739	0.3982	0.8739	0.9348
No log	6.6667	20	0.8395	0.3793	0.8395	0.9163
No log	7.3333	22	0.8292	0.4533	0.8292	0.9106
No log	8.0	24	0.8312	0.5259	0.8312	0.9117
No log	8.6667	26	0.8000	0.5183	0.8000	0.8944
No log	9.3333	28	0.7806	0.5098	0.7806	0.8835
No log	10.0	30	0.7443	0.5534	0.7443	0.8628
No log	10.6667	32	0.8044	0.4588	0.8044	0.8969
No log	11.3333	34	0.8928	0.4318	0.8928	0.9449
No log	12.0	36	0.8459	0.4466	0.8459	0.9197
No log	12.6667	38	0.7486	0.5485	0.7486	0.8652
No log	13.3333	40	0.7369	0.5660	0.7369	0.8585
No log	14.0	42	0.7317	0.5366	0.7317	0.8554
No log	14.6667	44	0.7368	0.6335	0.7368	0.8583
No log	15.3333	46	0.7387	0.6252	0.7387	0.8595
No log	16.0	48	0.7311	0.5701	0.7311	0.8550
No log	16.6667	50	0.7471	0.6460	0.7471	0.8643
No log	17.3333	52	0.7415	0.6460	0.7415	0.8611
No log	18.0	54	0.7156	0.6007	0.7156	0.8460
No log	18.6667	56	0.7162	0.5381	0.7162	0.8463
No log	19.3333	58	0.7284	0.5929	0.7284	0.8534
No log	20.0	60	0.7280	0.5752	0.7280	0.8532
No log	20.6667	62	0.7168	0.5651	0.7168	0.8466
No log	21.3333	64	0.7191	0.5651	0.7191	0.8480
No log	22.0	66	0.7738	0.6209	0.7738	0.8797
No log	22.6667	68	0.7729	0.6008	0.7729	0.8791
No log	23.3333	70	0.7339	0.5763	0.7339	0.8567
No log	24.0	72	0.7365	0.5763	0.7365	0.8582
No log	24.6667	74	0.7302	0.5980	0.7302	0.8545
No log	25.3333	76	0.7193	0.4720	0.7193	0.8481
No log	26.0	78	0.7206	0.5651	0.7206	0.8489
No log	26.6667	80	0.8314	0.5995	0.8314	0.9118
No log	27.3333	82	0.9325	0.5272	0.9325	0.9657
No log	28.0	84	0.7999	0.5989	0.7999	0.8943
No log	28.6667	86	0.7576	0.5528	0.7576	0.8704
No log	29.3333	88	0.7554	0.5434	0.7554	0.8692
No log	30.0	90	0.7623	0.5413	0.7623	0.8731
No log	30.6667	92	0.8217	0.5013	0.8217	0.9065
No log	31.3333	94	0.8822	0.4783	0.8822	0.9393
No log	32.0	96	0.8476	0.5222	0.8476	0.9207
No log	32.6667	98	0.7505	0.5877	0.7505	0.8663
No log	33.3333	100	0.7872	0.4186	0.7872	0.8872
No log	34.0	102	0.7775	0.4502	0.7775	0.8818
No log	34.6667	104	0.7419	0.5877	0.7419	0.8614
No log	35.3333	106	0.9102	0.5012	0.9102	0.9541
No log	36.0	108	1.1965	0.3494	1.1965	1.0939
No log	36.6667	110	1.2082	0.2731	1.2082	1.0992
No log	37.3333	112	1.0391	0.3095	1.0391	1.0194
No log	38.0	114	0.8784	0.4218	0.8784	0.9373
No log	38.6667	116	0.7620	0.5540	0.7620	0.8729
No log	39.3333	118	0.7845	0.4524	0.7845	0.8857
No log	40.0	120	0.7922	0.4524	0.7922	0.8901
No log	40.6667	122	0.7679	0.5632	0.7679	0.8763
No log	41.3333	124	0.8566	0.5353	0.8566	0.9255
No log	42.0	126	0.9944	0.4606	0.9944	0.9972
No log	42.6667	128	0.9844	0.4491	0.9844	0.9922
No log	43.3333	130	0.8471	0.5033	0.8471	0.9204
No log	44.0	132	0.7706	0.5626	0.7706	0.8778
No log	44.6667	134	0.7694	0.5626	0.7694	0.8772
No log	45.3333	136	0.7585	0.5752	0.7585	0.8709
No log	46.0	138	0.7687	0.5763	0.7687	0.8768
No log	46.6667	140	0.7695	0.5546	0.7695	0.8772
No log	47.3333	142	0.7849	0.5546	0.7849	0.8859
No log	48.0	144	0.8230	0.4590	0.8230	0.9072
No log	48.6667	146	0.8077	0.5054	0.8077	0.8987
No log	49.3333	148	0.8013	0.4604	0.8013	0.8952
No log	50.0	150	0.7665	0.5763	0.7665	0.8755
No log	50.6667	152	0.7655	0.5763	0.7655	0.8749
No log	51.3333	154	0.7737	0.5763	0.7737	0.8796
No log	52.0	156	0.7927	0.5422	0.7927	0.8904
No log	52.6667	158	0.8451	0.4720	0.8451	0.9193
No log	53.3333	160	0.8959	0.5006	0.8959	0.9465
No log	54.0	162	0.8699	0.4910	0.8699	0.9327
No log	54.6667	164	0.8168	0.4737	0.8168	0.9038
No log	55.3333	166	0.7843	0.5763	0.7843	0.8856
No log	56.0	168	0.7920	0.5331	0.7920	0.8899
No log	56.6667	170	0.8287	0.4696	0.8287	0.9103
No log	57.3333	172	0.8318	0.4696	0.8318	0.9120
No log	58.0	174	0.8364	0.4696	0.8364	0.9145
No log	58.6667	176	0.7983	0.5292	0.7983	0.8935
No log	59.3333	178	0.7715	0.5434	0.7715	0.8784
No log	60.0	180	0.7669	0.5221	0.7669	0.8757
No log	60.6667	182	0.7830	0.5291	0.7830	0.8849
No log	61.3333	184	0.7977	0.5292	0.7977	0.8931
No log	62.0	186	0.8217	0.4924	0.8217	0.9065
No log	62.6667	188	0.8131	0.5150	0.8131	0.9017
No log	63.3333	190	0.7801	0.5076	0.7801	0.8832
No log	64.0	192	0.7542	0.6007	0.7542	0.8684
No log	64.6667	194	0.7561	0.5688	0.7561	0.8696
No log	65.3333	196	0.7757	0.5429	0.7757	0.8807
No log	66.0	198	0.8101	0.4804	0.8101	0.9001
No log	66.6667	200	0.8252	0.4804	0.8252	0.9084
No log	67.3333	202	0.8261	0.4804	0.8261	0.9089
No log	68.0	204	0.8378	0.4681	0.8378	0.9153
No log	68.6667	206	0.8235	0.4455	0.8235	0.9075
No log	69.3333	208	0.7961	0.5279	0.7961	0.8922
No log	70.0	210	0.7586	0.5883	0.7586	0.8710
No log	70.6667	212	0.7531	0.5698	0.7531	0.8678
No log	71.3333	214	0.7593	0.5883	0.7593	0.8714
No log	72.0	216	0.7775	0.5516	0.7775	0.8817
No log	72.6667	218	0.8254	0.4920	0.8254	0.9085
No log	73.3333	220	0.8667	0.4994	0.8667	0.9310
No log	74.0	222	0.8794	0.4994	0.8794	0.9378
No log	74.6667	224	0.8842	0.4468	0.8842	0.9403
No log	75.3333	226	0.8533	0.4801	0.8533	0.9238
No log	76.0	228	0.8094	0.4965	0.8094	0.8997
No log	76.6667	230	0.7806	0.4862	0.7806	0.8835
No log	77.3333	232	0.7641	0.4888	0.7641	0.8741
No log	78.0	234	0.7586	0.4888	0.7586	0.8710
No log	78.6667	236	0.7580	0.4888	0.7580	0.8706
No log	79.3333	238	0.7654	0.5455	0.7654	0.8749
No log	80.0	240	0.7836	0.5455	0.7836	0.8852
No log	80.6667	242	0.8091	0.5048	0.8091	0.8995
No log	81.3333	244	0.8131	0.5048	0.8131	0.9017
No log	82.0	246	0.8027	0.4940	0.8027	0.8960
No log	82.6667	248	0.7926	0.4954	0.7926	0.8903
No log	83.3333	250	0.7850	0.4968	0.7850	0.8860
No log	84.0	252	0.7902	0.4954	0.7902	0.8890
No log	84.6667	254	0.8005	0.5292	0.8005	0.8947
No log	85.3333	256	0.8177	0.5160	0.8177	0.9043
No log	86.0	258	0.8257	0.5160	0.8257	0.9087
No log	86.6667	260	0.8226	0.5160	0.8226	0.9070
No log	87.3333	262	0.8144	0.5504	0.8144	0.9024
No log	88.0	264	0.7989	0.5482	0.7989	0.8938
No log	88.6667	266	0.7894	0.4853	0.7894	0.8885
No log	89.3333	268	0.7870	0.4853	0.7870	0.8871
No log	90.0	270	0.7826	0.4969	0.7826	0.8846
No log	90.6667	272	0.7815	0.4989	0.7815	0.8840
No log	91.3333	274	0.7848	0.4969	0.7848	0.8859
No log	92.0	276	0.7922	0.4969	0.7922	0.8901
No log	92.6667	278	0.8055	0.5163	0.8055	0.8975
No log	93.3333	280	0.8212	0.5487	0.8212	0.9062
No log	94.0	282	0.8396	0.4924	0.8396	0.9163
No log	94.6667	284	0.8541	0.4924	0.8541	0.9242
No log	95.3333	286	0.8611	0.5026	0.8611	0.9280
No log	96.0	288	0.8657	0.4807	0.8657	0.9304
No log	96.6667	290	0.8662	0.4807	0.8662	0.9307
No log	97.3333	292	0.8631	0.4807	0.8631	0.9291
No log	98.0	294	0.8583	0.5026	0.8583	0.9264
No log	98.6667	296	0.8531	0.5026	0.8531	0.9236
No log	99.3333	298	0.8500	0.5026	0.8500	0.9220
No log	100.0	300	0.8484	0.4924	0.8484	0.9211

Framework versions

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