ArabicNewSplits6_FineTuningAraBERT_run2_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: 0.7850
• Qwk: 0.4124
• Mse: 0.7850
• Rmse: 0.8860

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	4.2734	-0.0339	4.2734	2.0672
No log	0.125	4	2.3928	0.0035	2.3928	1.5469
No log	0.1875	6	1.5811	-0.0741	1.5811	1.2574
No log	0.25	8	1.0256	-0.0420	1.0256	1.0127
No log	0.3125	10	0.9568	0.0185	0.9568	0.9782
No log	0.375	12	0.7856	0.0307	0.7856	0.8864
No log	0.4375	14	0.7733	0.1363	0.7733	0.8794
No log	0.5	16	0.8905	0.0254	0.8905	0.9436
No log	0.5625	18	0.9639	0.0296	0.9639	0.9818
No log	0.625	20	1.0256	0.0545	1.0256	1.0127
No log	0.6875	22	0.8405	0.1733	0.8405	0.9168
No log	0.75	24	0.6782	0.2673	0.6782	0.8235
No log	0.8125	26	0.6405	0.2688	0.6405	0.8003
No log	0.875	28	0.6310	0.2333	0.6310	0.7943
No log	0.9375	30	0.6574	0.3333	0.6574	0.8108
No log	1.0	32	0.6893	0.2694	0.6893	0.8302
No log	1.0625	34	0.7416	0.2255	0.7416	0.8611
No log	1.125	36	0.7949	0.1751	0.7949	0.8915
No log	1.1875	38	0.7976	0.1643	0.7976	0.8931
No log	1.25	40	0.8987	0.1433	0.8987	0.9480
No log	1.3125	42	0.9349	0.1175	0.9349	0.9669
No log	1.375	44	0.8864	0.1948	0.8864	0.9415
No log	1.4375	46	1.0286	0.1649	1.0286	1.0142
No log	1.5	48	1.1216	0.1160	1.1216	1.0591
No log	1.5625	50	1.2672	0.1529	1.2672	1.1257
No log	1.625	52	1.2274	0.1606	1.2274	1.1079
No log	1.6875	54	1.0837	0.2003	1.0837	1.0410
No log	1.75	56	0.8650	0.1993	0.8650	0.9300
No log	1.8125	58	0.6634	0.3298	0.6634	0.8145
No log	1.875	60	0.5873	0.4113	0.5873	0.7664
No log	1.9375	62	0.6032	0.3327	0.6032	0.7766
No log	2.0	64	0.6918	0.2898	0.6918	0.8317
No log	2.0625	66	0.7933	0.2669	0.7933	0.8907
No log	2.125	68	1.1385	0.1434	1.1385	1.0670
No log	2.1875	70	1.2782	0.1572	1.2782	1.1306
No log	2.25	72	1.0033	0.2693	1.0033	1.0017
No log	2.3125	74	0.8431	0.2840	0.8431	0.9182
No log	2.375	76	0.6913	0.2969	0.6913	0.8314
No log	2.4375	78	0.6077	0.3794	0.6077	0.7795
No log	2.5	80	0.6143	0.4421	0.6143	0.7838
No log	2.5625	82	0.6876	0.3966	0.6876	0.8292
No log	2.625	84	0.7654	0.4078	0.7654	0.8749
No log	2.6875	86	0.9719	0.3607	0.9719	0.9858
No log	2.75	88	1.2387	0.2924	1.2387	1.1130
No log	2.8125	90	1.1809	0.2808	1.1809	1.0867
No log	2.875	92	0.9031	0.3964	0.9031	0.9503
No log	2.9375	94	0.7530	0.4204	0.7530	0.8677
No log	3.0	96	0.6228	0.4855	0.6228	0.7892
No log	3.0625	98	0.5776	0.4337	0.5776	0.7600
No log	3.125	100	0.5962	0.4407	0.5962	0.7721
No log	3.1875	102	0.6340	0.4380	0.6340	0.7962
No log	3.25	104	0.6952	0.4535	0.6952	0.8338
No log	3.3125	106	0.7446	0.4181	0.7446	0.8629
No log	3.375	108	0.7176	0.4853	0.7176	0.8471
No log	3.4375	110	0.7036	0.4957	0.7036	0.8388
No log	3.5	112	0.7155	0.4693	0.7155	0.8458
No log	3.5625	114	0.6702	0.4826	0.6702	0.8186
No log	3.625	116	0.6572	0.5255	0.6572	0.8107
No log	3.6875	118	0.6735	0.4826	0.6735	0.8207
No log	3.75	120	0.7911	0.4316	0.7911	0.8895
No log	3.8125	122	0.8584	0.3850	0.8584	0.9265
No log	3.875	124	0.8162	0.4191	0.8162	0.9034
No log	3.9375	126	0.6858	0.4924	0.6858	0.8281
No log	4.0	128	0.6589	0.4638	0.6589	0.8117
No log	4.0625	130	0.6538	0.4491	0.6538	0.8086
No log	4.125	132	0.6106	0.4716	0.6106	0.7814
No log	4.1875	134	0.5874	0.5171	0.5874	0.7664
No log	4.25	136	0.6566	0.5343	0.6566	0.8103
No log	4.3125	138	0.7076	0.5461	0.7076	0.8412
No log	4.375	140	0.6597	0.5259	0.6597	0.8122
No log	4.4375	142	0.6595	0.5124	0.6595	0.8121
No log	4.5	144	0.6678	0.4622	0.6678	0.8172
No log	4.5625	146	0.6754	0.5374	0.6754	0.8218
No log	4.625	148	0.6958	0.5012	0.6958	0.8341
No log	4.6875	150	0.7146	0.4080	0.7146	0.8453
No log	4.75	152	0.7272	0.4342	0.7272	0.8527
No log	4.8125	154	0.7459	0.4279	0.7459	0.8637
No log	4.875	156	0.7620	0.4224	0.7620	0.8729
No log	4.9375	158	0.7787	0.4224	0.7787	0.8824
No log	5.0	160	0.8116	0.4049	0.8116	0.9009
No log	5.0625	162	1.0442	0.3864	1.0442	1.0219
No log	5.125	164	1.3074	0.2990	1.3074	1.1434
No log	5.1875	166	1.2929	0.2908	1.2929	1.1371
No log	5.25	168	1.0968	0.3929	1.0968	1.0473
No log	5.3125	170	0.9047	0.4077	0.9047	0.9511
No log	5.375	172	0.8397	0.3944	0.8397	0.9163
No log	5.4375	174	0.8243	0.4349	0.8243	0.9079
No log	5.5	176	0.8075	0.4729	0.8075	0.8986
No log	5.5625	178	0.7770	0.4638	0.7770	0.8815
No log	5.625	180	0.7484	0.4654	0.7484	0.8651
No log	5.6875	182	0.7226	0.5154	0.7226	0.8500
No log	5.75	184	0.7201	0.4886	0.7201	0.8486
No log	5.8125	186	0.7072	0.5245	0.7072	0.8409
No log	5.875	188	0.7015	0.5314	0.7015	0.8375
No log	5.9375	190	0.7089	0.5222	0.7089	0.8420
No log	6.0	192	0.7347	0.4897	0.7347	0.8572
No log	6.0625	194	0.7716	0.4997	0.7716	0.8784
No log	6.125	196	0.8177	0.4686	0.8177	0.9043
No log	6.1875	198	0.8229	0.4686	0.8229	0.9071
No log	6.25	200	0.7897	0.4527	0.7897	0.8886
No log	6.3125	202	0.7593	0.4689	0.7593	0.8714
No log	6.375	204	0.7531	0.4530	0.7531	0.8678
No log	6.4375	206	0.7758	0.4930	0.7758	0.8808
No log	6.5	208	0.7746	0.4808	0.7746	0.8801
No log	6.5625	210	0.7606	0.4743	0.7606	0.8721
No log	6.625	212	0.7478	0.4486	0.7478	0.8648
No log	6.6875	214	0.7533	0.4297	0.7533	0.8679
No log	6.75	216	0.7607	0.4297	0.7607	0.8722
No log	6.8125	218	0.7535	0.4354	0.7535	0.8681
No log	6.875	220	0.7335	0.4103	0.7335	0.8564
No log	6.9375	222	0.7334	0.3986	0.7334	0.8564
No log	7.0	224	0.7238	0.3990	0.7238	0.8508
No log	7.0625	226	0.7104	0.4057	0.7104	0.8428
No log	7.125	228	0.6982	0.4161	0.6982	0.8356
No log	7.1875	230	0.7021	0.4018	0.7021	0.8379
No log	7.25	232	0.7051	0.4059	0.7051	0.8397
No log	7.3125	234	0.7168	0.4305	0.7168	0.8466
No log	7.375	236	0.7317	0.4502	0.7317	0.8554
No log	7.4375	238	0.7438	0.4502	0.7438	0.8625
No log	7.5	240	0.7508	0.4410	0.7508	0.8665
No log	7.5625	242	0.7501	0.4282	0.7501	0.8661
No log	7.625	244	0.7525	0.4298	0.7525	0.8675
No log	7.6875	246	0.7704	0.4277	0.7704	0.8777
No log	7.75	248	0.7912	0.4257	0.7912	0.8895
No log	7.8125	250	0.7982	0.4422	0.7982	0.8934
No log	7.875	252	0.7846	0.4384	0.7846	0.8858
No log	7.9375	254	0.7683	0.4406	0.7683	0.8765
No log	8.0	256	0.7499	0.4505	0.7499	0.8660
No log	8.0625	258	0.7452	0.4280	0.7452	0.8633
No log	8.125	260	0.7427	0.4415	0.7427	0.8618
No log	8.1875	262	0.7406	0.4222	0.7406	0.8606
No log	8.25	264	0.7424	0.4281	0.7424	0.8616
No log	8.3125	266	0.7458	0.4281	0.7458	0.8636
No log	8.375	268	0.7494	0.4337	0.7494	0.8657
No log	8.4375	270	0.7564	0.4220	0.7564	0.8697
No log	8.5	272	0.7700	0.4146	0.7700	0.8775
No log	8.5625	274	0.7758	0.4071	0.7758	0.8808
No log	8.625	276	0.7754	0.4071	0.7754	0.8806
No log	8.6875	278	0.7808	0.4048	0.7808	0.8836
No log	8.75	280	0.7749	0.4071	0.7749	0.8803
No log	8.8125	282	0.7703	0.4071	0.7703	0.8776
No log	8.875	284	0.7647	0.4087	0.7647	0.8745
No log	8.9375	286	0.7649	0.4083	0.7649	0.8746
No log	9.0	288	0.7659	0.4318	0.7659	0.8751
No log	9.0625	290	0.7665	0.4261	0.7665	0.8755
No log	9.125	292	0.7701	0.4200	0.7701	0.8776
No log	9.1875	294	0.7762	0.4141	0.7762	0.8810
No log	9.25	296	0.7840	0.4222	0.7840	0.8854
No log	9.3125	298	0.7900	0.4303	0.7900	0.8888
No log	9.375	300	0.7913	0.4162	0.7913	0.8896
No log	9.4375	302	0.7917	0.4222	0.7917	0.8898
No log	9.5	304	0.7903	0.4141	0.7903	0.8890
No log	9.5625	306	0.7881	0.4260	0.7881	0.8878
No log	9.625	308	0.7866	0.4260	0.7866	0.8869
No log	9.6875	310	0.7862	0.4260	0.7862	0.8867
No log	9.75	312	0.7855	0.4260	0.7855	0.8863
No log	9.8125	314	0.7852	0.4124	0.7852	0.8861
No log	9.875	316	0.7852	0.4124	0.7852	0.8861
No log	9.9375	318	0.7851	0.4124	0.7851	0.8860
No log	10.0	320	0.7850	0.4124	0.7850	0.8860

Framework versions

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