ArabicNewSplits6_FineTuningAraBERT_run1_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: 0.8206
• Qwk: 0.4270
• Mse: 0.8206
• Rmse: 0.9059

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	3.8030	-0.0078	3.8030	1.9501
No log	0.1111	4	2.0175	0.0372	2.0175	1.4204
No log	0.1667	6	1.2251	0.0355	1.2251	1.1068
No log	0.2222	8	1.1840	-0.0803	1.1840	1.0881
No log	0.2778	10	1.0398	-0.1552	1.0398	1.0197
No log	0.3333	12	1.0388	-0.1971	1.0388	1.0192
No log	0.3889	14	0.9809	-0.1237	0.9809	0.9904
No log	0.4444	16	1.3599	-0.0555	1.3599	1.1661
No log	0.5	18	1.3577	-0.0401	1.3577	1.1652
No log	0.5556	20	0.8608	0.0504	0.8608	0.9278
No log	0.6111	22	0.6914	0.2466	0.6914	0.8315
No log	0.6667	24	0.6822	0.2333	0.6822	0.8259
No log	0.7222	26	0.7119	0.2498	0.7119	0.8437
No log	0.7778	28	0.8751	0.0846	0.8751	0.9355
No log	0.8333	30	1.1373	0.0182	1.1373	1.0664
No log	0.8889	32	1.1079	0.0638	1.1079	1.0526
No log	0.9444	34	0.9487	0.0322	0.9487	0.9740
No log	1.0	36	0.7643	0.2333	0.7643	0.8742
No log	1.0556	38	0.6959	0.2947	0.6959	0.8342
No log	1.1111	40	0.7091	0.3104	0.7091	0.8421
No log	1.1667	42	0.8882	0.1793	0.8882	0.9424
No log	1.2222	44	1.0068	0.1559	1.0068	1.0034
No log	1.2778	46	0.9953	0.1669	0.9953	0.9977
No log	1.3333	48	0.8636	0.2315	0.8636	0.9293
No log	1.3889	50	0.6913	0.3649	0.6913	0.8315
No log	1.4444	52	0.6332	0.4315	0.6332	0.7957
No log	1.5	54	0.6543	0.4397	0.6543	0.8089
No log	1.5556	56	0.9349	0.2717	0.9349	0.9669
No log	1.6111	58	1.3128	0.2732	1.3128	1.1458
No log	1.6667	60	1.4122	0.1883	1.4122	1.1884
No log	1.7222	62	1.3809	0.1660	1.3809	1.1751
No log	1.7778	64	1.1586	0.1919	1.1586	1.0764
No log	1.8333	66	0.9143	0.2965	0.9143	0.9562
No log	1.8889	68	0.9471	0.1999	0.9471	0.9732
No log	1.9444	70	0.8622	0.2102	0.8622	0.9285
No log	2.0	72	0.6906	0.3796	0.6906	0.8310
No log	2.0556	74	0.5642	0.3386	0.5642	0.7511
No log	2.1111	76	0.5376	0.4276	0.5376	0.7332
No log	2.1667	78	0.5350	0.4632	0.5350	0.7314
No log	2.2222	80	0.5600	0.3247	0.5600	0.7483
No log	2.2778	82	0.6313	0.4241	0.6313	0.7945
No log	2.3333	84	0.9127	0.2818	0.9127	0.9553
No log	2.3889	86	0.8501	0.2941	0.8501	0.9220
No log	2.4444	88	0.6073	0.4040	0.6073	0.7793
No log	2.5	90	0.5786	0.4736	0.5786	0.7606
No log	2.5556	92	0.6095	0.4505	0.6095	0.7807
No log	2.6111	94	0.6523	0.4925	0.6523	0.8076
No log	2.6667	96	0.7782	0.5044	0.7782	0.8821
No log	2.7222	98	1.2153	0.3501	1.2153	1.1024
No log	2.7778	100	1.3530	0.2973	1.3530	1.1632
No log	2.8333	102	1.0098	0.4236	1.0098	1.0049
No log	2.8889	104	1.0113	0.4039	1.0113	1.0056
No log	2.9444	106	0.8261	0.4773	0.8261	0.9089
No log	3.0	108	0.6314	0.3956	0.6314	0.7946
No log	3.0556	110	0.5556	0.4757	0.5556	0.7454
No log	3.1111	112	0.5419	0.5016	0.5419	0.7362
No log	3.1667	114	0.5469	0.4757	0.5469	0.7395
No log	3.2222	116	0.6274	0.3983	0.6274	0.7921
No log	3.2778	118	0.8735	0.4021	0.8735	0.9346
No log	3.3333	120	0.9810	0.3947	0.9810	0.9904
No log	3.3889	122	0.8197	0.4551	0.8197	0.9054
No log	3.4444	124	0.6981	0.5321	0.6981	0.8355
No log	3.5	126	0.8336	0.4653	0.8336	0.9130
No log	3.5556	128	0.8553	0.4283	0.8553	0.9248
No log	3.6111	130	0.7508	0.4826	0.7508	0.8665
No log	3.6667	132	0.7128	0.4989	0.7128	0.8442
No log	3.7222	134	1.0224	0.4460	1.0224	1.0111
No log	3.7778	136	1.2874	0.3457	1.2874	1.1347
No log	3.8333	138	1.3340	0.3060	1.3340	1.1550
No log	3.8889	140	1.1229	0.4320	1.1229	1.0597
No log	3.9444	142	0.8232	0.4409	0.8232	0.9073
No log	4.0	144	0.6968	0.3917	0.6968	0.8348
No log	4.0556	146	0.6945	0.4043	0.6945	0.8334
No log	4.1111	148	0.7212	0.4312	0.7212	0.8492
No log	4.1667	150	0.7167	0.4656	0.7167	0.8466
No log	4.2222	152	0.7718	0.4555	0.7718	0.8785
No log	4.2778	154	0.7788	0.4628	0.7788	0.8825
No log	4.3333	156	0.7509	0.4716	0.7509	0.8666
No log	4.3889	158	0.7771	0.4203	0.7771	0.8816
No log	4.4444	160	0.7910	0.4425	0.7910	0.8894
No log	4.5	162	0.7882	0.4451	0.7882	0.8878
No log	4.5556	164	0.7942	0.4791	0.7942	0.8912
No log	4.6111	166	0.8440	0.4651	0.8440	0.9187
No log	4.6667	168	0.9485	0.4045	0.9485	0.9739
No log	4.7222	170	0.9623	0.4085	0.9623	0.9809
No log	4.7778	172	0.8931	0.4164	0.8931	0.9451
No log	4.8333	174	0.8988	0.4218	0.8988	0.9480
No log	4.8889	176	0.8465	0.4479	0.8465	0.9200
No log	4.9444	178	0.8078	0.4868	0.8078	0.8988
No log	5.0	180	0.8311	0.4537	0.8311	0.9117
No log	5.0556	182	0.8832	0.4423	0.8832	0.9398
No log	5.1111	184	0.8623	0.4331	0.8623	0.9286
No log	5.1667	186	0.8195	0.4193	0.8195	0.9053
No log	5.2222	188	0.8406	0.4767	0.8406	0.9168
No log	5.2778	190	0.9229	0.4344	0.9229	0.9607
No log	5.3333	192	0.9484	0.4175	0.9484	0.9738
No log	5.3889	194	1.0143	0.3993	1.0143	1.0071
No log	5.4444	196	1.0157	0.4160	1.0157	1.0078
No log	5.5	198	0.9665	0.4022	0.9665	0.9831
No log	5.5556	200	0.8455	0.4845	0.8455	0.9195
No log	5.6111	202	0.7908	0.4679	0.7908	0.8892
No log	5.6667	204	0.7760	0.4442	0.7760	0.8809
No log	5.7222	206	0.7774	0.5005	0.7774	0.8817
No log	5.7778	208	0.8507	0.4585	0.8507	0.9223
No log	5.8333	210	0.9333	0.3999	0.9333	0.9661
No log	5.8889	212	0.9044	0.4259	0.9044	0.9510
No log	5.9444	214	0.8072	0.5098	0.8072	0.8985
No log	6.0	216	0.7528	0.4637	0.7528	0.8676
No log	6.0556	218	0.7479	0.4623	0.7479	0.8648
No log	6.1111	220	0.7577	0.4782	0.7577	0.8704
No log	6.1667	222	0.8413	0.4645	0.8413	0.9172
No log	6.2222	224	0.8985	0.4259	0.8985	0.9479
No log	6.2778	226	0.8926	0.4313	0.8926	0.9448
No log	6.3333	228	0.8636	0.4422	0.8636	0.9293
No log	6.3889	230	0.8132	0.4803	0.8132	0.9017
No log	6.4444	232	0.8051	0.4928	0.8051	0.8973
No log	6.5	234	0.7909	0.4854	0.7909	0.8893
No log	6.5556	236	0.7604	0.4886	0.7604	0.8720
No log	6.6111	238	0.7371	0.4621	0.7371	0.8586
No log	6.6667	240	0.7315	0.5147	0.7315	0.8553
No log	6.7222	242	0.7705	0.5211	0.7705	0.8778
No log	6.7778	244	0.7696	0.5211	0.7696	0.8773
No log	6.8333	246	0.7391	0.5195	0.7391	0.8597
No log	6.8889	248	0.7227	0.4953	0.7227	0.8501
No log	6.9444	250	0.7875	0.5075	0.7875	0.8874
No log	7.0	252	0.8794	0.4647	0.8794	0.9378
No log	7.0556	254	0.9046	0.4314	0.9046	0.9511
No log	7.1111	256	0.8470	0.4843	0.8470	0.9203
No log	7.1667	258	0.7628	0.4537	0.7628	0.8734
No log	7.2222	260	0.7168	0.4700	0.7168	0.8466
No log	7.2778	262	0.7157	0.5037	0.7157	0.8460
No log	7.3333	264	0.7258	0.4564	0.7258	0.8519
No log	7.3889	266	0.7642	0.5034	0.7642	0.8742
No log	7.4444	268	0.7984	0.4740	0.7984	0.8935
No log	7.5	270	0.8289	0.4814	0.8289	0.9105
No log	7.5556	272	0.8114	0.4921	0.8114	0.9008
No log	7.6111	274	0.7926	0.4960	0.7926	0.8903
No log	7.6667	276	0.7809	0.4752	0.7809	0.8837
No log	7.7222	278	0.7882	0.4776	0.7882	0.8878
No log	7.7778	280	0.8046	0.4749	0.8046	0.8970
No log	7.8333	282	0.8222	0.4564	0.8222	0.9068
No log	7.8889	284	0.8640	0.4362	0.8640	0.9295
No log	7.9444	286	0.9046	0.4218	0.9046	0.9511
No log	8.0	288	0.9157	0.4237	0.9157	0.9569
No log	8.0556	290	0.8990	0.4166	0.8990	0.9481
No log	8.1111	292	0.8578	0.4552	0.8578	0.9262
No log	8.1667	294	0.8417	0.4537	0.8417	0.9174
No log	8.2222	296	0.8362	0.4165	0.8362	0.9144
No log	8.2778	298	0.8324	0.4183	0.8324	0.9123
No log	8.3333	300	0.8257	0.4219	0.8257	0.9087
No log	8.3889	302	0.8273	0.4243	0.8273	0.9095
No log	8.4444	304	0.8491	0.4540	0.8491	0.9215
No log	8.5	306	0.8927	0.4291	0.8927	0.9448
No log	8.5556	308	0.9155	0.3902	0.9155	0.9568
No log	8.6111	310	0.9050	0.3954	0.9050	0.9513
No log	8.6667	312	0.8990	0.3954	0.8990	0.9482
No log	8.7222	314	0.8883	0.4273	0.8883	0.9425
No log	8.7778	316	0.8703	0.4326	0.8703	0.9329
No log	8.8333	318	0.8588	0.4435	0.8588	0.9267
No log	8.8889	320	0.8430	0.4325	0.8430	0.9181
No log	8.9444	322	0.8254	0.4479	0.8254	0.9085
No log	9.0	324	0.8160	0.4667	0.8160	0.9033
No log	9.0556	326	0.8046	0.4653	0.8046	0.8970
No log	9.1111	328	0.7973	0.4556	0.7973	0.8929
No log	9.1667	330	0.7936	0.4698	0.7936	0.8908
No log	9.2222	332	0.7921	0.4776	0.7921	0.8900
No log	9.2778	334	0.7944	0.4776	0.7944	0.8913
No log	9.3333	336	0.7955	0.4717	0.7955	0.8919
No log	9.3889	338	0.8029	0.4250	0.8029	0.8961
No log	9.4444	340	0.8140	0.4477	0.8140	0.9022
No log	9.5	342	0.8200	0.4623	0.8200	0.9056
No log	9.5556	344	0.8280	0.4512	0.8280	0.9100
No log	9.6111	346	0.8310	0.4384	0.8310	0.9116
No log	9.6667	348	0.8333	0.4384	0.8333	0.9128
No log	9.7222	350	0.8317	0.4512	0.8317	0.9120
No log	9.7778	352	0.8289	0.4438	0.8289	0.9104
No log	9.8333	354	0.8252	0.4435	0.8252	0.9084
No log	9.8889	356	0.8229	0.4417	0.8229	0.9072
No log	9.9444	358	0.8213	0.4270	0.8213	0.9062
No log	10.0	360	0.8206	0.4270	0.8206	0.9059

Framework versions

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