ArabicNewSplits6_FineTuningAraBERT_run1_AugV5_k6_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: 0.8321
• Qwk: 0.4956
• Mse: 0.8321
• Rmse: 0.9122

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	0.0625	2	4.3847	-0.0284	4.3847	2.0940
No log	0.125	4	2.5044	-0.0244	2.5044	1.5825
No log	0.1875	6	2.3361	-0.1062	2.3361	1.5284
No log	0.25	8	1.2470	0.0256	1.2470	1.1167
No log	0.3125	10	0.8943	0.0271	0.8943	0.9456
No log	0.375	12	0.8500	0.0417	0.8500	0.9220
No log	0.4375	14	0.7830	0.1092	0.7830	0.8849
No log	0.5	16	0.9820	0.0822	0.9820	0.9909
No log	0.5625	18	1.1718	0.0944	1.1718	1.0825
No log	0.625	20	0.7661	0.2874	0.7661	0.8753
No log	0.6875	22	0.6971	0.3042	0.6971	0.8349
No log	0.75	24	0.8465	0.2315	0.8465	0.9201
No log	0.8125	26	1.3679	0.1695	1.3679	1.1696
No log	0.875	28	1.4878	0.1630	1.4878	1.2197
No log	0.9375	30	1.0856	0.25	1.0856	1.0419
No log	1.0	32	0.8628	0.2624	0.8628	0.9289
No log	1.0625	34	0.8442	0.2624	0.8442	0.9188
No log	1.125	36	0.8309	0.2752	0.8309	0.9115
No log	1.1875	38	0.7655	0.3346	0.7655	0.8749
No log	1.25	40	0.8682	0.3327	0.8682	0.9318
No log	1.3125	42	0.8090	0.4062	0.8090	0.8995
No log	1.375	44	0.8376	0.4204	0.8376	0.9152
No log	1.4375	46	0.7088	0.4520	0.7088	0.8419
No log	1.5	48	0.6910	0.4872	0.6910	0.8313
No log	1.5625	50	0.6592	0.5409	0.6592	0.8119
No log	1.625	52	0.6569	0.5315	0.6569	0.8105
No log	1.6875	54	0.6754	0.5188	0.6754	0.8218
No log	1.75	56	0.7473	0.4813	0.7473	0.8644
No log	1.8125	58	0.7702	0.4754	0.7702	0.8776
No log	1.875	60	0.6768	0.5039	0.6768	0.8227
No log	1.9375	62	0.6374	0.5456	0.6374	0.7983
No log	2.0	64	0.7510	0.4402	0.7510	0.8666
No log	2.0625	66	0.7497	0.4540	0.7497	0.8659
No log	2.125	68	0.6606	0.5370	0.6606	0.8128
No log	2.1875	70	0.8583	0.4334	0.8583	0.9264
No log	2.25	72	1.0855	0.3571	1.0855	1.0419
No log	2.3125	74	1.1507	0.3617	1.1507	1.0727
No log	2.375	76	0.9986	0.4270	0.9986	0.9993
No log	2.4375	78	0.7769	0.5080	0.7769	0.8814
No log	2.5	80	0.7029	0.5165	0.7029	0.8384
No log	2.5625	82	0.7379	0.4468	0.7379	0.8590
No log	2.625	84	0.7228	0.4289	0.7228	0.8502
No log	2.6875	86	0.6571	0.4766	0.6571	0.8106
No log	2.75	88	0.6314	0.5007	0.6314	0.7946
No log	2.8125	90	0.6545	0.4719	0.6545	0.8090
No log	2.875	92	0.6577	0.4847	0.6577	0.8110
No log	2.9375	94	0.6791	0.5155	0.6791	0.8241
No log	3.0	96	0.7238	0.5091	0.7238	0.8508
No log	3.0625	98	0.8582	0.4259	0.8582	0.9264
No log	3.125	100	1.0801	0.4168	1.0801	1.0393
No log	3.1875	102	1.1285	0.4144	1.1285	1.0623
No log	3.25	104	1.0220	0.4507	1.0220	1.0109
No log	3.3125	106	0.9261	0.4693	0.9261	0.9623
No log	3.375	108	0.9189	0.4507	0.9189	0.9586
No log	3.4375	110	0.9466	0.4669	0.9466	0.9729
No log	3.5	112	0.9541	0.4929	0.9541	0.9768
No log	3.5625	114	0.9381	0.4942	0.9381	0.9686
No log	3.625	116	0.8996	0.4918	0.8996	0.9485
No log	3.6875	118	0.8455	0.5043	0.8455	0.9195
No log	3.75	120	0.8139	0.4992	0.8139	0.9022
No log	3.8125	122	0.7838	0.4929	0.7838	0.8853
No log	3.875	124	0.7449	0.5195	0.7449	0.8631
No log	3.9375	126	0.7211	0.5217	0.7211	0.8492
No log	4.0	128	0.7219	0.4838	0.7219	0.8497
No log	4.0625	130	0.7218	0.4986	0.7218	0.8496
No log	4.125	132	0.7399	0.5085	0.7399	0.8602
No log	4.1875	134	0.7785	0.5171	0.7785	0.8823
No log	4.25	136	0.8140	0.5319	0.8140	0.9022
No log	4.3125	138	0.8588	0.4982	0.8588	0.9267
No log	4.375	140	0.8667	0.5084	0.8667	0.9310
No log	4.4375	142	0.8555	0.4896	0.8555	0.9249
No log	4.5	144	0.8647	0.4997	0.8647	0.9299
No log	4.5625	146	0.8770	0.4663	0.8770	0.9365
No log	4.625	148	0.8768	0.5134	0.8768	0.9364
No log	4.6875	150	0.8746	0.4802	0.8746	0.9352
No log	4.75	152	0.8613	0.4762	0.8613	0.9281
No log	4.8125	154	0.8467	0.4865	0.8467	0.9202
No log	4.875	156	0.8160	0.4737	0.8160	0.9033
No log	4.9375	158	0.8189	0.4710	0.8189	0.9050
No log	5.0	160	0.8377	0.4589	0.8377	0.9153
No log	5.0625	162	0.8572	0.4654	0.8572	0.9258
No log	5.125	164	0.8595	0.4803	0.8595	0.9271
No log	5.1875	166	0.8959	0.4728	0.8959	0.9465
No log	5.25	168	0.9049	0.4836	0.9049	0.9513
No log	5.3125	170	0.8739	0.4555	0.8739	0.9348
No log	5.375	172	0.8604	0.5110	0.8604	0.9276
No log	5.4375	174	0.8466	0.4819	0.8466	0.9201
No log	5.5	176	0.8398	0.4574	0.8398	0.9164
No log	5.5625	178	0.8162	0.5140	0.8162	0.9034
No log	5.625	180	0.7977	0.5278	0.7977	0.8932
No log	5.6875	182	0.7931	0.5088	0.7931	0.8906
No log	5.75	184	0.7829	0.5244	0.7829	0.8848
No log	5.8125	186	0.7890	0.5195	0.7890	0.8883
No log	5.875	188	0.8013	0.4915	0.8013	0.8951
No log	5.9375	190	0.8275	0.5211	0.8275	0.9097
No log	6.0	192	0.8505	0.5172	0.8505	0.9222
No log	6.0625	194	0.8356	0.4984	0.8356	0.9141
No log	6.125	196	0.8642	0.5061	0.8642	0.9296
No log	6.1875	198	0.9190	0.4557	0.9190	0.9586
No log	6.25	200	0.9511	0.4564	0.9511	0.9752
No log	6.3125	202	0.9457	0.4627	0.9457	0.9725
No log	6.375	204	0.9570	0.5145	0.9570	0.9783
No log	6.4375	206	0.9700	0.4904	0.9700	0.9849
No log	6.5	208	0.9680	0.5125	0.9680	0.9838
No log	6.5625	210	0.9767	0.4920	0.9767	0.9883
No log	6.625	212	0.9658	0.5090	0.9658	0.9828
No log	6.6875	214	0.9588	0.4560	0.9588	0.9792
No log	6.75	216	0.9556	0.4561	0.9556	0.9775
No log	6.8125	218	0.9227	0.4548	0.9227	0.9606
No log	6.875	220	0.8628	0.4800	0.8628	0.9289
No log	6.9375	222	0.8276	0.4651	0.8276	0.9097
No log	7.0	224	0.8214	0.4811	0.8214	0.9063
No log	7.0625	226	0.8179	0.4753	0.8179	0.9044
No log	7.125	228	0.8140	0.4741	0.8140	0.9022
No log	7.1875	230	0.8129	0.4821	0.8129	0.9016
No log	7.25	232	0.8168	0.4801	0.8168	0.9038
No log	7.3125	234	0.8252	0.4778	0.8252	0.9084
No log	7.375	236	0.8302	0.4669	0.8302	0.9112
No log	7.4375	238	0.8357	0.4675	0.8357	0.9142
No log	7.5	240	0.8564	0.4918	0.8564	0.9254
No log	7.5625	242	0.8729	0.4990	0.8729	0.9343
No log	7.625	244	0.8748	0.4670	0.8748	0.9353
No log	7.6875	246	0.8828	0.4554	0.8828	0.9396
No log	7.75	248	0.9203	0.4619	0.9203	0.9593
No log	7.8125	250	0.9761	0.4238	0.9761	0.9880
No log	7.875	252	0.9913	0.4387	0.9913	0.9956
No log	7.9375	254	0.9648	0.4123	0.9648	0.9822
No log	8.0	256	0.9233	0.4540	0.9233	0.9609
No log	8.0625	258	0.8833	0.4816	0.8833	0.9398
No log	8.125	260	0.8653	0.4675	0.8653	0.9302
No log	8.1875	262	0.8553	0.4863	0.8553	0.9248
No log	8.25	264	0.8479	0.4663	0.8479	0.9208
No log	8.3125	266	0.8380	0.4821	0.8380	0.9155
No log	8.375	268	0.8292	0.4956	0.8292	0.9106
No log	8.4375	270	0.8270	0.4730	0.8270	0.9094
No log	8.5	272	0.8223	0.4740	0.8223	0.9068
No log	8.5625	274	0.8172	0.4844	0.8172	0.9040
No log	8.625	276	0.8076	0.4971	0.8076	0.8986
No log	8.6875	278	0.7982	0.4979	0.7982	0.8934
No log	8.75	280	0.7956	0.4963	0.7956	0.8920
No log	8.8125	282	0.8021	0.4948	0.8021	0.8956
No log	8.875	284	0.8136	0.4743	0.8136	0.9020
No log	8.9375	286	0.8241	0.4674	0.8241	0.9078
No log	9.0	288	0.8257	0.4743	0.8257	0.9087
No log	9.0625	290	0.8242	0.4748	0.8242	0.9079
No log	9.125	292	0.8219	0.4956	0.8219	0.9066
No log	9.1875	294	0.8260	0.4956	0.8260	0.9088
No log	9.25	296	0.8302	0.4633	0.8302	0.9112
No log	9.3125	298	0.8316	0.4885	0.8316	0.9119
No log	9.375	300	0.8335	0.4762	0.8335	0.9129
No log	9.4375	302	0.8330	0.4762	0.8330	0.9127
No log	9.5	304	0.8298	0.4629	0.8298	0.9109
No log	9.5625	306	0.8264	0.4853	0.8264	0.9091
No log	9.625	308	0.8251	0.4853	0.8251	0.9084
No log	9.6875	310	0.8260	0.4956	0.8260	0.9088
No log	9.75	312	0.8289	0.4956	0.8289	0.9104
No log	9.8125	314	0.8311	0.4956	0.8311	0.9116
No log	9.875	316	0.8319	0.4956	0.8319	0.9121
No log	9.9375	318	0.8321	0.4956	0.8321	0.9122
No log	10.0	320	0.8321	0.4956	0.8321	0.9122

Framework versions

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