ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k7_task1_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: 0.5938
• Qwk: 0.7204
• Mse: 0.5938
• Rmse: 0.7706

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	5.1604	-0.0580	5.1604	2.2716
No log	0.1111	4	3.2832	0.0498	3.2832	1.8119
No log	0.1667	6	2.2467	-0.0548	2.2467	1.4989
No log	0.2222	8	1.7138	0.0273	1.7138	1.3091
No log	0.2778	10	1.2481	0.1799	1.2481	1.1172
No log	0.3333	12	1.2395	0.2227	1.2395	1.1133
No log	0.3889	14	1.3963	0.0293	1.3963	1.1816
No log	0.4444	16	1.3827	0.0338	1.3827	1.1759
No log	0.5	18	1.6792	0.0065	1.6792	1.2958
No log	0.5556	20	1.6440	0.0065	1.6440	1.2822
No log	0.6111	22	1.6490	0.0585	1.6490	1.2842
No log	0.6667	24	1.1954	0.2785	1.1954	1.0934
No log	0.7222	26	1.0644	0.2354	1.0644	1.0317
No log	0.7778	28	1.0153	0.2632	1.0153	1.0076
No log	0.8333	30	0.9559	0.3228	0.9559	0.9777
No log	0.8889	32	0.9618	0.4240	0.9618	0.9807
No log	0.9444	34	1.3525	0.2407	1.3525	1.1630
No log	1.0	36	1.8793	0.2009	1.8793	1.3709
No log	1.0556	38	2.0811	0.2565	2.0811	1.4426
No log	1.1111	40	1.7548	0.2043	1.7548	1.3247
No log	1.1667	42	1.1799	0.3397	1.1799	1.0862
No log	1.2222	44	0.8771	0.4913	0.8771	0.9365
No log	1.2778	46	0.8106	0.4321	0.8106	0.9003
No log	1.3333	48	0.8167	0.5388	0.8167	0.9037
No log	1.3889	50	0.9735	0.5087	0.9735	0.9867
No log	1.4444	52	1.1353	0.4633	1.1353	1.0655
No log	1.5	54	1.1090	0.4644	1.1090	1.0531
No log	1.5556	56	0.8685	0.5387	0.8685	0.9319
No log	1.6111	58	0.6996	0.5520	0.6996	0.8364
No log	1.6667	60	0.6836	0.5898	0.6836	0.8268
No log	1.7222	62	0.6719	0.6390	0.6719	0.8197
No log	1.7778	64	0.7864	0.6150	0.7864	0.8868
No log	1.8333	66	1.1123	0.4868	1.1123	1.0547
No log	1.8889	68	1.1489	0.5039	1.1489	1.0719
No log	1.9444	70	0.9097	0.5869	0.9097	0.9538
No log	2.0	72	0.7026	0.6519	0.7026	0.8382
No log	2.0556	74	0.7819	0.6248	0.7819	0.8843
No log	2.1111	76	1.0601	0.5277	1.0601	1.0296
No log	2.1667	78	1.2526	0.5257	1.2526	1.1192
No log	2.2222	80	1.0901	0.5148	1.0901	1.0441
No log	2.2778	82	0.6960	0.6742	0.6960	0.8343
No log	2.3333	84	0.6893	0.7309	0.6893	0.8303
No log	2.3889	86	0.7240	0.7129	0.7240	0.8509
No log	2.4444	88	0.6108	0.7296	0.6108	0.7816
No log	2.5	90	0.8076	0.6415	0.8076	0.8986
No log	2.5556	92	1.1085	0.5460	1.1085	1.0528
No log	2.6111	94	1.0661	0.5606	1.0661	1.0325
No log	2.6667	96	0.8372	0.5879	0.8372	0.9150
No log	2.7222	98	0.6871	0.6558	0.6871	0.8289
No log	2.7778	100	0.5642	0.7562	0.5642	0.7511
No log	2.8333	102	0.5526	0.7586	0.5526	0.7433
No log	2.8889	104	0.6175	0.6863	0.6175	0.7858
No log	2.9444	106	0.8733	0.5705	0.8733	0.9345
No log	3.0	108	0.8690	0.5705	0.8690	0.9322
No log	3.0556	110	0.6993	0.6418	0.6993	0.8362
No log	3.1111	112	0.6054	0.7052	0.6054	0.7781
No log	3.1667	114	0.6083	0.7124	0.6083	0.7799
No log	3.2222	116	0.6896	0.6894	0.6896	0.8304
No log	3.2778	118	0.9551	0.5570	0.9551	0.9773
No log	3.3333	120	1.2481	0.5191	1.2481	1.1172
No log	3.3889	122	1.1565	0.5401	1.1565	1.0754
No log	3.4444	124	0.8075	0.6644	0.8075	0.8986
No log	3.5	126	0.5949	0.7482	0.5949	0.7713
No log	3.5556	128	0.5831	0.7415	0.5831	0.7636
No log	3.6111	130	0.5840	0.7334	0.5840	0.7642
No log	3.6667	132	0.5965	0.7126	0.5965	0.7723
No log	3.7222	134	0.6793	0.6969	0.6793	0.8242
No log	3.7778	136	0.8090	0.6447	0.8090	0.8995
No log	3.8333	138	0.7322	0.6520	0.7322	0.8557
No log	3.8889	140	0.6042	0.7156	0.6042	0.7773
No log	3.9444	142	0.5823	0.7149	0.5823	0.7631
No log	4.0	144	0.5833	0.7355	0.5833	0.7637
No log	4.0556	146	0.5835	0.7353	0.5835	0.7639
No log	4.1111	148	0.6624	0.6838	0.6624	0.8139
No log	4.1667	150	0.6608	0.6880	0.6608	0.8129
No log	4.2222	152	0.6334	0.7178	0.6334	0.7958
No log	4.2778	154	0.6039	0.7201	0.6039	0.7771
No log	4.3333	156	0.5984	0.7296	0.5984	0.7736
No log	4.3889	158	0.6025	0.7280	0.6025	0.7762
No log	4.4444	160	0.6283	0.7133	0.6283	0.7927
No log	4.5	162	0.6523	0.6917	0.6523	0.8076
No log	4.5556	164	0.6282	0.7144	0.6282	0.7926
No log	4.6111	166	0.6089	0.7367	0.6089	0.7803
No log	4.6667	168	0.6366	0.7081	0.6366	0.7979
No log	4.7222	170	0.6603	0.7051	0.6603	0.8126
No log	4.7778	172	0.6364	0.6949	0.6364	0.7977
No log	4.8333	174	0.6414	0.7318	0.6414	0.8009
No log	4.8889	176	0.6842	0.6936	0.6842	0.8272
No log	4.9444	178	0.7281	0.6789	0.7281	0.8533
No log	5.0	180	0.7104	0.6906	0.7104	0.8428
No log	5.0556	182	0.6632	0.7289	0.6632	0.8144
No log	5.1111	184	0.6703	0.7175	0.6703	0.8187
No log	5.1667	186	0.6990	0.7179	0.6990	0.8361
No log	5.2222	188	0.6781	0.6907	0.6781	0.8235
No log	5.2778	190	0.6525	0.7219	0.6525	0.8078
No log	5.3333	192	0.6485	0.6964	0.6485	0.8053
No log	5.3889	194	0.6557	0.7132	0.6557	0.8097
No log	5.4444	196	0.6569	0.7053	0.6569	0.8105
No log	5.5	198	0.6493	0.7038	0.6493	0.8058
No log	5.5556	200	0.6346	0.6770	0.6346	0.7966
No log	5.6111	202	0.6284	0.7065	0.6284	0.7927
No log	5.6667	204	0.6285	0.7145	0.6285	0.7928
No log	5.7222	206	0.6264	0.7132	0.6264	0.7915
No log	5.7778	208	0.6320	0.7248	0.6320	0.7950
No log	5.8333	210	0.6304	0.7405	0.6304	0.7940
No log	5.8889	212	0.6350	0.7498	0.6350	0.7968
No log	5.9444	214	0.6377	0.7428	0.6377	0.7986
No log	6.0	216	0.6305	0.7461	0.6305	0.7940
No log	6.0556	218	0.6408	0.7252	0.6408	0.8005
No log	6.1111	220	0.6904	0.6794	0.6904	0.8309
No log	6.1667	222	0.6786	0.6770	0.6786	0.8238
No log	6.2222	224	0.6552	0.6898	0.6552	0.8095
No log	6.2778	226	0.6110	0.7298	0.6110	0.7817
No log	6.3333	228	0.5962	0.7433	0.5962	0.7722
No log	6.3889	230	0.6221	0.7183	0.6221	0.7888
No log	6.4444	232	0.6239	0.7183	0.6239	0.7899
No log	6.5	234	0.6123	0.7305	0.6123	0.7825
No log	6.5556	236	0.6002	0.7395	0.6002	0.7747
No log	6.6111	238	0.6122	0.7255	0.6122	0.7824
No log	6.6667	240	0.6187	0.7261	0.6187	0.7866
No log	6.7222	242	0.6276	0.7126	0.6276	0.7922
No log	6.7778	244	0.6322	0.7147	0.6322	0.7951
No log	6.8333	246	0.6173	0.7021	0.6173	0.7857
No log	6.8889	248	0.6144	0.7445	0.6144	0.7839
No log	6.9444	250	0.6221	0.7422	0.6221	0.7888
No log	7.0	252	0.6251	0.7422	0.6251	0.7906
No log	7.0556	254	0.6239	0.7194	0.6239	0.7899
No log	7.1111	256	0.6228	0.6933	0.6228	0.7892
No log	7.1667	258	0.6405	0.6916	0.6405	0.8003
No log	7.2222	260	0.6728	0.6455	0.6728	0.8202
No log	7.2778	262	0.6586	0.6944	0.6586	0.8115
No log	7.3333	264	0.6253	0.6902	0.6253	0.7907
No log	7.3889	266	0.6172	0.7176	0.6172	0.7856
No log	7.4444	268	0.6178	0.7216	0.6178	0.7860
No log	7.5	270	0.6196	0.7292	0.6196	0.7872
No log	7.5556	272	0.6201	0.7248	0.6201	0.7874
No log	7.6111	274	0.6197	0.7227	0.6197	0.7872
No log	7.6667	276	0.6206	0.7227	0.6206	0.7878
No log	7.7222	278	0.6223	0.7058	0.6223	0.7888
No log	7.7778	280	0.6194	0.7064	0.6194	0.7870
No log	7.8333	282	0.6136	0.7286	0.6136	0.7833
No log	7.8889	284	0.6111	0.7225	0.6111	0.7817
No log	7.9444	286	0.6054	0.7241	0.6054	0.7781
No log	8.0	288	0.6034	0.7224	0.6034	0.7768
No log	8.0556	290	0.6009	0.7347	0.6009	0.7752
No log	8.1111	292	0.5947	0.7110	0.5947	0.7712
No log	8.1667	294	0.5986	0.7076	0.5986	0.7737
No log	8.2222	296	0.6080	0.7199	0.6080	0.7797
No log	8.2778	298	0.6151	0.7109	0.6151	0.7843
No log	8.3333	300	0.6100	0.7223	0.6100	0.7810
No log	8.3889	302	0.6126	0.7201	0.6126	0.7827
No log	8.4444	304	0.6191	0.7049	0.6191	0.7868
No log	8.5	306	0.6169	0.7207	0.6169	0.7855
No log	8.5556	308	0.6072	0.7387	0.6072	0.7792
No log	8.6111	310	0.6031	0.7549	0.6031	0.7766
No log	8.6667	312	0.6017	0.7362	0.6017	0.7757
No log	8.7222	314	0.6023	0.7270	0.6023	0.7761
No log	8.7778	316	0.6023	0.7270	0.6023	0.7761
No log	8.8333	318	0.6014	0.7495	0.6014	0.7755
No log	8.8889	320	0.6021	0.7570	0.6021	0.7759
No log	8.9444	322	0.6020	0.7570	0.6020	0.7759
No log	9.0	324	0.6008	0.7613	0.6008	0.7751
No log	9.0556	326	0.5996	0.7314	0.5996	0.7744
No log	9.1111	328	0.5999	0.7155	0.5999	0.7745
No log	9.1667	330	0.6001	0.7265	0.6001	0.7747
No log	9.2222	332	0.6020	0.7265	0.6020	0.7759
No log	9.2778	334	0.6040	0.7265	0.6040	0.7771
No log	9.3333	336	0.6083	0.7204	0.6083	0.7800
No log	9.3889	338	0.6092	0.7204	0.6092	0.7805
No log	9.4444	340	0.6068	0.7204	0.6068	0.7790
No log	9.5	342	0.6039	0.7204	0.6039	0.7771
No log	9.5556	344	0.6041	0.7204	0.6041	0.7772
No log	9.6111	346	0.6029	0.7204	0.6029	0.7764
No log	9.6667	348	0.6016	0.7204	0.6016	0.7756
No log	9.7222	350	0.5989	0.7204	0.5989	0.7739
No log	9.7778	352	0.5964	0.7204	0.5964	0.7723
No log	9.8333	354	0.5954	0.7204	0.5954	0.7716
No log	9.8889	356	0.5945	0.7204	0.5945	0.7710
No log	9.9444	358	0.5940	0.7204	0.5940	0.7707
No log	10.0	360	0.5938	0.7204	0.5938	0.7706

Framework versions

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