ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run1_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: 0.7056
• Qwk: 0.7343
• Mse: 0.7056
• Rmse: 0.8400

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	0.0588	2	2.1313	0.0058	2.1313	1.4599
No log	0.1176	4	1.4901	0.1780	1.4901	1.2207
No log	0.1765	6	1.6805	0.1558	1.6805	1.2963
No log	0.2353	8	1.6928	0.3329	1.6928	1.3011
No log	0.2941	10	1.4401	0.3101	1.4401	1.2000
No log	0.3529	12	1.6527	0.2793	1.6527	1.2856
No log	0.4118	14	2.2742	0.2268	2.2742	1.5080
No log	0.4706	16	2.3072	0.1875	2.3072	1.5190
No log	0.5294	18	1.7047	0.2913	1.7047	1.3056
No log	0.5882	20	1.3697	0.1817	1.3697	1.1703
No log	0.6471	22	1.3370	0.1817	1.3370	1.1563
No log	0.7059	24	1.2618	0.2604	1.2618	1.1233
No log	0.7647	26	1.1922	0.3334	1.1922	1.0919
No log	0.8235	28	1.3263	0.3845	1.3263	1.1516
No log	0.8824	30	1.4950	0.3589	1.4950	1.2227
No log	0.9412	32	1.3841	0.3614	1.3841	1.1765
No log	1.0	34	1.2307	0.4268	1.2307	1.1094
No log	1.0588	36	1.2209	0.4980	1.2209	1.1050
No log	1.1176	38	1.0476	0.5447	1.0476	1.0235
No log	1.1765	40	0.9350	0.6401	0.9350	0.9670
No log	1.2353	42	0.8011	0.6107	0.8011	0.8951
No log	1.2941	44	0.7916	0.6241	0.7916	0.8897
No log	1.3529	46	0.8183	0.6272	0.8183	0.9046
No log	1.4118	48	0.8969	0.6684	0.8969	0.9470
No log	1.4706	50	1.1769	0.5886	1.1769	1.0848
No log	1.5294	52	1.0514	0.6255	1.0514	1.0254
No log	1.5882	54	0.7963	0.6419	0.7963	0.8924
No log	1.6471	56	0.7984	0.6146	0.7984	0.8935
No log	1.7059	58	0.7791	0.6371	0.7791	0.8827
No log	1.7647	60	0.8113	0.6674	0.8113	0.9007
No log	1.8235	62	1.1066	0.6377	1.1066	1.0520
No log	1.8824	64	1.3201	0.5823	1.3201	1.1490
No log	1.9412	66	1.2004	0.5924	1.2004	1.0956
No log	2.0	68	0.8897	0.6681	0.8897	0.9433
No log	2.0588	70	0.7337	0.6649	0.7337	0.8565
No log	2.1176	72	0.7211	0.6841	0.7211	0.8492
No log	2.1765	74	0.7732	0.6901	0.7732	0.8793
No log	2.2353	76	0.8566	0.6839	0.8566	0.9255
No log	2.2941	78	0.9783	0.6332	0.9783	0.9891
No log	2.3529	80	1.2068	0.5553	1.2068	1.0985
No log	2.4118	82	1.1669	0.5572	1.1669	1.0802
No log	2.4706	84	1.0182	0.5735	1.0182	1.0091
No log	2.5294	86	0.8635	0.6177	0.8635	0.9292
No log	2.5882	88	0.7578	0.6391	0.7578	0.8705
No log	2.6471	90	0.7540	0.6419	0.7540	0.8683
No log	2.7059	92	0.8384	0.6571	0.8384	0.9157
No log	2.7647	94	1.1172	0.5659	1.1172	1.0570
No log	2.8235	96	1.3079	0.5295	1.3079	1.1436
No log	2.8824	98	1.3171	0.5164	1.3171	1.1477
No log	2.9412	100	1.0647	0.5767	1.0647	1.0318
No log	3.0	102	0.8308	0.6641	0.8308	0.9115
No log	3.0588	104	0.7812	0.6908	0.7812	0.8839
No log	3.1176	106	0.7588	0.7020	0.7588	0.8711
No log	3.1765	108	0.8347	0.6933	0.8347	0.9136
No log	3.2353	110	0.9252	0.6844	0.9252	0.9619
No log	3.2941	112	0.9015	0.7088	0.9015	0.9495
No log	3.3529	114	0.8006	0.7333	0.8006	0.8947
No log	3.4118	116	0.6985	0.7040	0.6985	0.8358
No log	3.4706	118	0.6865	0.6905	0.6865	0.8286
No log	3.5294	120	0.7326	0.7116	0.7326	0.8559
No log	3.5882	122	0.7589	0.7363	0.7589	0.8712
No log	3.6471	124	0.7197	0.7151	0.7197	0.8484
No log	3.7059	126	0.7113	0.7032	0.7113	0.8434
No log	3.7647	128	0.7457	0.7161	0.7457	0.8636
No log	3.8235	130	0.7758	0.7172	0.7758	0.8808
No log	3.8824	132	0.7434	0.7234	0.7434	0.8622
No log	3.9412	134	0.7336	0.7293	0.7336	0.8565
No log	4.0	136	0.7377	0.7247	0.7377	0.8589
No log	4.0588	138	0.7247	0.7207	0.7247	0.8513
No log	4.1176	140	0.7350	0.7010	0.7350	0.8573
No log	4.1765	142	0.8145	0.6961	0.8145	0.9025
No log	4.2353	144	0.8800	0.6995	0.8800	0.9381
No log	4.2941	146	0.8750	0.6995	0.8750	0.9354
No log	4.3529	148	0.8293	0.6945	0.8293	0.9107
No log	4.4118	150	0.7435	0.7371	0.7435	0.8623
No log	4.4706	152	0.6773	0.7201	0.6773	0.8230
No log	4.5294	154	0.6479	0.7183	0.6479	0.8049
No log	4.5882	156	0.6460	0.7161	0.6460	0.8037
No log	4.6471	158	0.6869	0.7416	0.6869	0.8288
No log	4.7059	160	0.8074	0.7523	0.8074	0.8986
No log	4.7647	162	0.9978	0.6732	0.9978	0.9989
No log	4.8235	164	1.0752	0.6519	1.0752	1.0369
No log	4.8824	166	0.9989	0.6575	0.9989	0.9995
No log	4.9412	168	0.8332	0.7302	0.8332	0.9128
No log	5.0	170	0.7519	0.7523	0.7519	0.8671
No log	5.0588	172	0.7510	0.7490	0.7510	0.8666
No log	5.1176	174	0.7788	0.7344	0.7788	0.8825
No log	5.1765	176	0.7616	0.7309	0.7616	0.8727
No log	5.2353	178	0.7263	0.7446	0.7263	0.8522
No log	5.2941	180	0.7022	0.7460	0.7022	0.8380
No log	5.3529	182	0.7071	0.7519	0.7071	0.8409
No log	5.4118	184	0.7252	0.7421	0.7252	0.8516
No log	5.4706	186	0.7755	0.7402	0.7755	0.8806
No log	5.5294	188	0.7992	0.7281	0.7992	0.8940
No log	5.5882	190	0.7932	0.7321	0.7932	0.8906
No log	5.6471	192	0.8428	0.6882	0.8428	0.9180
No log	5.7059	194	0.8636	0.6815	0.8636	0.9293
No log	5.7647	196	0.8162	0.7054	0.8162	0.9034
No log	5.8235	198	0.7298	0.7576	0.7298	0.8543
No log	5.8824	200	0.6655	0.7405	0.6655	0.8158
No log	5.9412	202	0.6516	0.7390	0.6516	0.8072
No log	6.0	204	0.6734	0.7484	0.6734	0.8206
No log	6.0588	206	0.7001	0.7512	0.7001	0.8367
No log	6.1176	208	0.7353	0.7344	0.7353	0.8575
No log	6.1765	210	0.7674	0.7392	0.7674	0.8760
No log	6.2353	212	0.7312	0.7629	0.7312	0.8551
No log	6.2941	214	0.6754	0.7396	0.6754	0.8218
No log	6.3529	216	0.6363	0.7078	0.6363	0.7977
No log	6.4118	218	0.6244	0.7235	0.6244	0.7902
No log	6.4706	220	0.6229	0.7213	0.6229	0.7893
No log	6.5294	222	0.6335	0.7099	0.6335	0.7959
No log	6.5882	224	0.6705	0.7335	0.6705	0.8189
No log	6.6471	226	0.6949	0.7511	0.6949	0.8336
No log	6.7059	228	0.7232	0.7592	0.7232	0.8504
No log	6.7647	230	0.7466	0.7354	0.7466	0.8640
No log	6.8235	232	0.7465	0.7390	0.7465	0.8640
No log	6.8824	234	0.7710	0.7139	0.7710	0.8781
No log	6.9412	236	0.7796	0.7173	0.7796	0.8830
No log	7.0	238	0.7498	0.7231	0.7498	0.8659
No log	7.0588	240	0.7515	0.7266	0.7515	0.8669
No log	7.1176	242	0.7486	0.7266	0.7486	0.8652
No log	7.1765	244	0.7617	0.7266	0.7617	0.8727
No log	7.2353	246	0.7849	0.7173	0.7849	0.8860
No log	7.2941	248	0.7811	0.7173	0.7811	0.8838
No log	7.3529	250	0.7636	0.7158	0.7636	0.8738
No log	7.4118	252	0.7436	0.7081	0.7436	0.8623
No log	7.4706	254	0.7112	0.7466	0.7112	0.8433
No log	7.5294	256	0.7039	0.7515	0.7039	0.8390
No log	7.5882	258	0.7112	0.7356	0.7112	0.8433
No log	7.6471	260	0.7114	0.7355	0.7114	0.8434
No log	7.7059	262	0.7356	0.7416	0.7356	0.8577
No log	7.7647	264	0.7783	0.7235	0.7783	0.8822
No log	7.8235	266	0.8032	0.7215	0.8032	0.8962
No log	7.8824	268	0.7881	0.7214	0.7881	0.8878
No log	7.9412	270	0.7624	0.7234	0.7624	0.8731
No log	8.0	272	0.7462	0.7105	0.7462	0.8638
No log	8.0588	274	0.7429	0.7187	0.7429	0.8619
No log	8.1176	276	0.7339	0.7266	0.7339	0.8567
No log	8.1765	278	0.7362	0.7266	0.7362	0.8580
No log	8.2353	280	0.7318	0.7187	0.7318	0.8555
No log	8.2941	282	0.7258	0.7273	0.7258	0.8519
No log	8.3529	284	0.7295	0.7529	0.7295	0.8541
No log	8.4118	286	0.7257	0.7350	0.7257	0.8519
No log	8.4706	288	0.7176	0.7529	0.7176	0.8471
No log	8.5294	290	0.7242	0.7350	0.7242	0.8510
No log	8.5882	292	0.7179	0.7315	0.7179	0.8473
No log	8.6471	294	0.7093	0.7412	0.7093	0.8422
No log	8.7059	296	0.6975	0.7570	0.6975	0.8352
No log	8.7647	298	0.6915	0.7612	0.6915	0.8316
No log	8.8235	300	0.6861	0.7576	0.6861	0.8283
No log	8.8824	302	0.6793	0.7576	0.6793	0.8242
No log	8.9412	304	0.6808	0.7612	0.6808	0.8251
No log	9.0	306	0.6868	0.7612	0.6868	0.8288
No log	9.0588	308	0.6888	0.7570	0.6888	0.8300
No log	9.1176	310	0.6984	0.7450	0.6984	0.8357
No log	9.1765	312	0.7088	0.7407	0.7088	0.8419
No log	9.2353	314	0.7115	0.7286	0.7115	0.8435
No log	9.2941	316	0.7177	0.7343	0.7177	0.8472
No log	9.3529	318	0.7204	0.7493	0.7204	0.8488
No log	9.4118	320	0.7164	0.7379	0.7164	0.8464
No log	9.4706	322	0.7140	0.7343	0.7140	0.8450
No log	9.5294	324	0.7131	0.7343	0.7131	0.8445
No log	9.5882	326	0.7075	0.7343	0.7075	0.8411
No log	9.6471	328	0.7046	0.7286	0.7046	0.8394
No log	9.7059	330	0.7014	0.7286	0.7014	0.8375
No log	9.7647	332	0.7005	0.7286	0.7005	0.8370
No log	9.8235	334	0.7017	0.7286	0.7017	0.8377
No log	9.8824	336	0.7039	0.7343	0.7039	0.8390
No log	9.9412	338	0.7053	0.7343	0.7053	0.8398
No log	10.0	340	0.7056	0.7343	0.7056	0.8400

Framework versions

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