ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run3_AugV5_k1_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: 1.4547
• Qwk: 0.4603
• Mse: 1.4547
• Rmse: 1.2061

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	0.5	2	6.8174	0.0242	6.8174	2.6110
No log	1.0	4	4.5971	0.0690	4.5971	2.1441
No log	1.5	6	3.3125	0.0238	3.3125	1.8200
No log	2.0	8	2.5306	0.0556	2.5306	1.5908
No log	2.5	10	1.8020	0.1869	1.8020	1.3424
No log	3.0	12	1.6368	0.1887	1.6368	1.2794
No log	3.5	14	1.6175	0.1509	1.6175	1.2718
No log	4.0	16	1.6731	0.1524	1.6731	1.2935
No log	4.5	18	1.6103	0.0971	1.6103	1.2690
No log	5.0	20	1.5276	0.0784	1.5276	1.2360
No log	5.5	22	1.5572	0.2182	1.5572	1.2479
No log	6.0	24	1.5751	0.2182	1.5751	1.2550
No log	6.5	26	1.4601	0.2037	1.4601	1.2084
No log	7.0	28	1.7074	0.2075	1.7074	1.3067
No log	7.5	30	2.2306	0.0185	2.2306	1.4935
No log	8.0	32	2.0906	0.0893	2.0906	1.4459
No log	8.5	34	1.9482	0.1207	1.9482	1.3958
No log	9.0	36	1.5947	0.4320	1.5947	1.2628
No log	9.5	38	1.4011	0.3540	1.4011	1.1837
No log	10.0	40	1.3890	0.1869	1.3890	1.1785
No log	10.5	42	1.4435	0.2342	1.4435	1.2014
No log	11.0	44	1.4752	0.2182	1.4752	1.2146
No log	11.5	46	1.4280	0.2342	1.4280	1.1950
No log	12.0	48	1.4148	0.1852	1.4148	1.1895
No log	12.5	50	1.3517	0.2182	1.3517	1.1626
No log	13.0	52	1.2570	0.3898	1.2570	1.1211
No log	13.5	54	1.2267	0.4833	1.2267	1.1076
No log	14.0	56	1.2831	0.4793	1.2831	1.1328
No log	14.5	58	1.5241	0.3680	1.5241	1.2346
No log	15.0	60	1.6500	0.3150	1.6500	1.2845
No log	15.5	62	1.5657	0.3150	1.5657	1.2513
No log	16.0	64	1.4352	0.4516	1.4352	1.1980
No log	16.5	66	1.2365	0.496	1.2365	1.1120
No log	17.0	68	1.2732	0.496	1.2732	1.1284
No log	17.5	70	1.4399	0.368	1.4398	1.1999
No log	18.0	72	1.6003	0.3256	1.6003	1.2650
No log	18.5	74	1.6527	0.3125	1.6527	1.2856
No log	19.0	76	1.5812	0.3492	1.5812	1.2575
No log	19.5	78	1.4702	0.3248	1.4702	1.2125
No log	20.0	80	1.4503	0.3130	1.4503	1.2043
No log	20.5	82	1.4726	0.3559	1.4726	1.2135
No log	21.0	84	1.4834	0.3226	1.4834	1.2179
No log	21.5	86	1.4375	0.4098	1.4375	1.1989
No log	22.0	88	1.4755	0.3906	1.4755	1.2147
No log	22.5	90	1.6002	0.3636	1.6002	1.2650
No log	23.0	92	1.6562	0.3206	1.6562	1.2869
No log	23.5	94	1.6020	0.3910	1.6020	1.2657
No log	24.0	96	1.3729	0.5079	1.3729	1.1717
No log	24.5	98	1.3132	0.3077	1.3132	1.1459
No log	25.0	100	1.3877	0.2523	1.3877	1.1780
No log	25.5	102	1.3783	0.3276	1.3783	1.1740
No log	26.0	104	1.4817	0.4286	1.4817	1.2173
No log	26.5	106	1.5767	0.4	1.5767	1.2557
No log	27.0	108	1.5827	0.3937	1.5827	1.2580
No log	27.5	110	1.5431	0.4	1.5431	1.2422
No log	28.0	112	1.4801	0.3361	1.4801	1.2166
No log	28.5	114	1.4381	0.3967	1.4381	1.1992
No log	29.0	116	1.4902	0.3968	1.4902	1.2207
No log	29.5	118	1.4988	0.4375	1.4988	1.2242
No log	30.0	120	1.4701	0.4444	1.4701	1.2125
No log	30.5	122	1.4123	0.4590	1.4123	1.1884
No log	31.0	124	1.3722	0.4298	1.3722	1.1714
No log	31.5	126	1.3619	0.4426	1.3619	1.1670
No log	32.0	128	1.4264	0.4219	1.4264	1.1943
No log	32.5	130	1.5234	0.3788	1.5234	1.2343
No log	33.0	132	1.6059	0.3538	1.6059	1.2673
No log	33.5	134	1.6217	0.3538	1.6217	1.2735
No log	34.0	136	1.5737	0.3538	1.5737	1.2545
No log	34.5	138	1.4459	0.4127	1.4459	1.2025
No log	35.0	140	1.4009	0.4553	1.4009	1.1836
No log	35.5	142	1.4471	0.4882	1.4471	1.2030
No log	36.0	144	1.4949	0.4688	1.4949	1.2226
No log	36.5	146	1.4823	0.4567	1.4823	1.2175
No log	37.0	148	1.4331	0.3590	1.4331	1.1971
No log	37.5	150	1.4053	0.3419	1.4053	1.1855
No log	38.0	152	1.3974	0.3866	1.3974	1.1821
No log	38.5	154	1.4170	0.4127	1.4170	1.1904
No log	39.0	156	1.4822	0.4615	1.4822	1.2175
No log	39.5	158	1.4988	0.4545	1.4988	1.2243
No log	40.0	160	1.4513	0.4375	1.4513	1.2047
No log	40.5	162	1.3903	0.4839	1.3903	1.1791
No log	41.0	164	1.3735	0.4839	1.3735	1.1720
No log	41.5	166	1.3727	0.4839	1.3727	1.1716
No log	42.0	168	1.3704	0.4839	1.3704	1.1707
No log	42.5	170	1.3491	0.4839	1.3491	1.1615
No log	43.0	172	1.4050	0.4444	1.4050	1.1853
No log	43.5	174	1.5454	0.4091	1.5454	1.2432
No log	44.0	176	1.5794	0.3817	1.5794	1.2567
No log	44.5	178	1.4785	0.4091	1.4785	1.2159
No log	45.0	180	1.3993	0.4715	1.3993	1.1829
No log	45.5	182	1.3803	0.4426	1.3803	1.1749
No log	46.0	184	1.4046	0.4426	1.4046	1.1852
No log	46.5	186	1.4309	0.4	1.4309	1.1962
No log	47.0	188	1.4997	0.4032	1.4997	1.2246
No log	47.5	190	1.5675	0.3438	1.5675	1.2520
No log	48.0	192	1.5970	0.3150	1.5970	1.2637
No log	48.5	194	1.5634	0.3810	1.5634	1.2504
No log	49.0	196	1.5037	0.3667	1.5037	1.2263
No log	49.5	198	1.4891	0.3667	1.4891	1.2203
No log	50.0	200	1.4772	0.3866	1.4772	1.2154
No log	50.5	202	1.5009	0.4228	1.5009	1.2251
No log	51.0	204	1.5472	0.3721	1.5472	1.2439
No log	51.5	206	1.6029	0.4148	1.6029	1.2660
No log	52.0	208	1.5840	0.4148	1.5840	1.2586
No log	52.5	210	1.5173	0.4328	1.5173	1.2318
No log	53.0	212	1.4205	0.3876	1.4205	1.1919
No log	53.5	214	1.3429	0.4590	1.3429	1.1588
No log	54.0	216	1.3475	0.4590	1.3475	1.1608
No log	54.5	218	1.3795	0.4590	1.3795	1.1745
No log	55.0	220	1.4301	0.4032	1.4301	1.1959
No log	55.5	222	1.4914	0.4186	1.4914	1.2212
No log	56.0	224	1.5723	0.3906	1.5723	1.2539
No log	56.5	226	1.5762	0.3721	1.5762	1.2555
No log	57.0	228	1.5203	0.3968	1.5203	1.2330
No log	57.5	230	1.4495	0.3934	1.4495	1.2040
No log	58.0	232	1.3923	0.3932	1.3923	1.1799
No log	58.5	234	1.3799	0.3793	1.3799	1.1747
No log	59.0	236	1.3675	0.3826	1.3675	1.1694
No log	59.5	238	1.3463	0.3898	1.3463	1.1603
No log	60.0	240	1.3480	0.4463	1.3480	1.1610
No log	60.5	242	1.3608	0.4590	1.3608	1.1665
No log	61.0	244	1.3980	0.4715	1.3980	1.1824
No log	61.5	246	1.4286	0.48	1.4286	1.1952
No log	62.0	248	1.4785	0.4462	1.4785	1.2159
No log	62.5	250	1.4790	0.4409	1.4790	1.2161
No log	63.0	252	1.4631	0.4320	1.4631	1.2096
No log	63.5	254	1.4589	0.4194	1.4589	1.2078
No log	64.0	256	1.4686	0.4194	1.4686	1.2119
No log	64.5	258	1.4768	0.4194	1.4768	1.2152
No log	65.0	260	1.4956	0.4194	1.4956	1.2229
No log	65.5	262	1.5177	0.4094	1.5177	1.2319
No log	66.0	264	1.5310	0.4219	1.5310	1.2373
No log	66.5	266	1.5037	0.4094	1.5037	1.2263
No log	67.0	268	1.4574	0.4516	1.4574	1.2072
No log	67.5	270	1.4588	0.4480	1.4588	1.2078
No log	68.0	272	1.4803	0.4375	1.4803	1.2167
No log	68.5	274	1.4779	0.4496	1.4779	1.2157
No log	69.0	276	1.4844	0.4462	1.4844	1.2184
No log	69.5	278	1.4991	0.4462	1.4991	1.2244
No log	70.0	280	1.4804	0.4462	1.4804	1.2167
No log	70.5	282	1.4350	0.4496	1.4350	1.1979
No log	71.0	284	1.3830	0.4677	1.3830	1.1760
No log	71.5	286	1.3728	0.4426	1.3728	1.1717
No log	72.0	288	1.3836	0.4426	1.3836	1.1763
No log	72.5	290	1.4088	0.4426	1.4088	1.1869
No log	73.0	292	1.4470	0.4426	1.4470	1.2029
No log	73.5	294	1.4852	0.4677	1.4852	1.2187
No log	74.0	296	1.5282	0.4320	1.5282	1.2362
No log	74.5	298	1.5413	0.4219	1.5413	1.2415
No log	75.0	300	1.5246	0.4409	1.5246	1.2347
No log	75.5	302	1.4936	0.4320	1.4936	1.2221
No log	76.0	304	1.4530	0.4603	1.4530	1.2054
No log	76.5	306	1.4093	0.4320	1.4093	1.1872
No log	77.0	308	1.3907	0.4320	1.3907	1.1793
No log	77.5	310	1.3857	0.4603	1.3857	1.1771
No log	78.0	312	1.3902	0.4603	1.3902	1.1790
No log	78.5	314	1.3885	0.4603	1.3885	1.1784
No log	79.0	316	1.3968	0.4688	1.3968	1.1819
No log	79.5	318	1.4038	0.4688	1.4038	1.1848
No log	80.0	320	1.4156	0.4688	1.4156	1.1898
No log	80.5	322	1.4060	0.4567	1.4060	1.1857
No log	81.0	324	1.3842	0.48	1.3842	1.1765
No log	81.5	326	1.3799	0.4839	1.3799	1.1747
No log	82.0	328	1.3903	0.48	1.3903	1.1791
No log	82.5	330	1.4154	0.4603	1.4154	1.1897
No log	83.0	332	1.4312	0.4567	1.4312	1.1963
No log	83.5	334	1.4416	0.4567	1.4416	1.2007
No log	84.0	336	1.4455	0.4567	1.4455	1.2023
No log	84.5	338	1.4421	0.4688	1.4421	1.2009
No log	85.0	340	1.4505	0.4651	1.4505	1.2044
No log	85.5	342	1.4627	0.4651	1.4627	1.2094
No log	86.0	344	1.4754	0.4462	1.4754	1.2147
No log	86.5	346	1.4917	0.4462	1.4917	1.2213
No log	87.0	348	1.4917	0.4275	1.4917	1.2213
No log	87.5	350	1.4746	0.4462	1.4746	1.2143
No log	88.0	352	1.4485	0.4651	1.4485	1.2035
No log	88.5	354	1.4358	0.4688	1.4358	1.1982
No log	89.0	356	1.4290	0.4567	1.4290	1.1954
No log	89.5	358	1.4322	0.4567	1.4322	1.1968
No log	90.0	360	1.4391	0.4688	1.4391	1.1996
No log	90.5	362	1.4484	0.4651	1.4484	1.2035
No log	91.0	364	1.4620	0.4462	1.4620	1.2092
No log	91.5	366	1.4820	0.4275	1.4820	1.2174
No log	92.0	368	1.4905	0.4275	1.4905	1.2209
No log	92.5	370	1.4914	0.4275	1.4914	1.2212
No log	93.0	372	1.4822	0.4275	1.4822	1.2175
No log	93.5	374	1.4725	0.4651	1.4725	1.2135
No log	94.0	376	1.4624	0.4651	1.4624	1.2093
No log	94.5	378	1.4572	0.4651	1.4572	1.2071
No log	95.0	380	1.4529	0.4567	1.4529	1.2054
No log	95.5	382	1.4540	0.4603	1.4540	1.2058
No log	96.0	384	1.4534	0.4603	1.4534	1.2056
No log	96.5	386	1.4533	0.4603	1.4533	1.2055
No log	97.0	388	1.4524	0.4603	1.4524	1.2051
No log	97.5	390	1.4516	0.4603	1.4516	1.2048
No log	98.0	392	1.4517	0.4603	1.4517	1.2049
No log	98.5	394	1.4530	0.4603	1.4530	1.2054
No log	99.0	396	1.4546	0.4603	1.4546	1.2061
No log	99.5	398	1.4546	0.4603	1.4546	1.2061
No log	100.0	400	1.4547	0.4603	1.4547	1.2061

Framework versions

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