ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k5_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: 1.0013
• Qwk: 0.4730
• Mse: 1.0013
• Rmse: 1.0006

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	0.0714	2	3.7363	0.0038	3.7363	1.9329
No log	0.1429	4	1.8671	0.0287	1.8671	1.3664
No log	0.2143	6	1.0654	0.0602	1.0654	1.0322
No log	0.2857	8	0.7212	0.1989	0.7212	0.8493
No log	0.3571	10	0.8901	0.1385	0.8901	0.9435
No log	0.4286	12	0.9571	0.0352	0.9571	0.9783
No log	0.5	14	0.8028	0.1762	0.8028	0.8960
No log	0.5714	16	0.9145	0.1917	0.9145	0.9563
No log	0.6429	18	1.0497	0.2279	1.0497	1.0245
No log	0.7143	20	0.8953	0.0909	0.8953	0.9462
No log	0.7857	22	0.8852	0.0387	0.8852	0.9408
No log	0.8571	24	0.7669	0.0535	0.7669	0.8757
No log	0.9286	26	0.7063	0.1208	0.7063	0.8404
No log	1.0	28	0.6904	0.1063	0.6904	0.8309
No log	1.0714	30	0.7313	0.1063	0.7313	0.8551
No log	1.1429	32	0.7734	0.1640	0.7734	0.8794
No log	1.2143	34	0.8398	0.2212	0.8398	0.9164
No log	1.2857	36	0.6964	0.1834	0.6964	0.8345
No log	1.3571	38	0.6776	0.2530	0.6776	0.8231
No log	1.4286	40	0.7171	0.3019	0.7171	0.8468
No log	1.5	42	0.6605	0.1534	0.6605	0.8127
No log	1.5714	44	0.6969	0.1599	0.6969	0.8348
No log	1.6429	46	0.7212	0.2087	0.7212	0.8493
No log	1.7143	48	0.7904	0.2360	0.7904	0.8890
No log	1.7857	50	0.9215	0.3138	0.9215	0.9599
No log	1.8571	52	0.8383	0.3049	0.8383	0.9156
No log	1.9286	54	0.6258	0.3552	0.6258	0.7910
No log	2.0	56	0.5766	0.4255	0.5766	0.7593
No log	2.0714	58	0.5790	0.4338	0.5790	0.7610
No log	2.1429	60	0.5700	0.4204	0.5700	0.7550
No log	2.2143	62	0.5770	0.4359	0.5770	0.7596
No log	2.2857	64	0.6295	0.4795	0.6295	0.7934
No log	2.3571	66	0.6886	0.4763	0.6886	0.8298
No log	2.4286	68	0.7792	0.4437	0.7792	0.8827
No log	2.5	70	0.7256	0.4533	0.7256	0.8518
No log	2.5714	72	0.7524	0.4454	0.7524	0.8674
No log	2.6429	74	0.8502	0.3647	0.8502	0.9221
No log	2.7143	76	0.9450	0.3787	0.9450	0.9721
No log	2.7857	78	0.9760	0.3792	0.9760	0.9879
No log	2.8571	80	0.9642	0.3849	0.9642	0.9820
No log	2.9286	82	0.9658	0.3921	0.9658	0.9827
No log	3.0	84	0.8425	0.4262	0.8425	0.9179
No log	3.0714	86	0.7273	0.5459	0.7273	0.8528
No log	3.1429	88	0.6948	0.5418	0.6948	0.8336
No log	3.2143	90	0.7605	0.5407	0.7605	0.8720
No log	3.2857	92	0.9194	0.4857	0.9194	0.9589
No log	3.3571	94	1.1331	0.4159	1.1331	1.0645
No log	3.4286	96	1.1660	0.4062	1.1660	1.0798
No log	3.5	98	1.0913	0.4233	1.0913	1.0446
No log	3.5714	100	0.9862	0.5208	0.9862	0.9931
No log	3.6429	102	0.9517	0.5026	0.9517	0.9755
No log	3.7143	104	1.0828	0.5235	1.0828	1.0406
No log	3.7857	106	1.3057	0.4177	1.3057	1.1427
No log	3.8571	108	1.1554	0.5104	1.1554	1.0749
No log	3.9286	110	0.8942	0.5148	0.8942	0.9456
No log	4.0	112	0.8265	0.4827	0.8265	0.9091
No log	4.0714	114	0.8953	0.4916	0.8953	0.9462
No log	4.1429	116	1.1000	0.5177	1.1000	1.0488
No log	4.2143	118	1.0718	0.4958	1.0718	1.0353
No log	4.2857	120	0.9629	0.5137	0.9629	0.9813
No log	4.3571	122	0.9037	0.5204	0.9037	0.9506
No log	4.4286	124	0.8414	0.5002	0.8414	0.9173
No log	4.5	126	0.8672	0.4889	0.8672	0.9312
No log	4.5714	128	0.8825	0.5159	0.8825	0.9394
No log	4.6429	130	0.8990	0.5025	0.8990	0.9482
No log	4.7143	132	0.8774	0.4881	0.8774	0.9367
No log	4.7857	134	0.9513	0.4856	0.9513	0.9753
No log	4.8571	136	1.2584	0.4699	1.2584	1.1218
No log	4.9286	138	1.4071	0.4064	1.4071	1.1862
No log	5.0	140	1.2609	0.4712	1.2609	1.1229
No log	5.0714	142	1.0649	0.4714	1.0649	1.0320
No log	5.1429	144	0.9511	0.4724	0.9511	0.9753
No log	5.2143	146	0.9368	0.4752	0.9368	0.9679
No log	5.2857	148	1.0156	0.4534	1.0156	1.0078
No log	5.3571	150	1.3247	0.3713	1.3247	1.1510
No log	5.4286	152	1.6439	0.3275	1.6439	1.2821
No log	5.5	154	1.6433	0.3261	1.6433	1.2819
No log	5.5714	156	1.4442	0.3507	1.4442	1.2017
No log	5.6429	158	1.1259	0.4173	1.1259	1.0611
No log	5.7143	160	0.9697	0.4751	0.9697	0.9847
No log	5.7857	162	0.9320	0.4895	0.9320	0.9654
No log	5.8571	164	0.9893	0.4683	0.9893	0.9946
No log	5.9286	166	1.1586	0.4565	1.1586	1.0764
No log	6.0	168	1.2124	0.4317	1.2124	1.1011
No log	6.0714	170	1.1725	0.4600	1.1725	1.0828
No log	6.1429	172	1.1008	0.4698	1.1008	1.0492
No log	6.2143	174	1.0172	0.4780	1.0172	1.0086
No log	6.2857	176	0.9142	0.5161	0.9142	0.9562
No log	6.3571	178	0.8674	0.5145	0.8674	0.9313
No log	6.4286	180	0.8702	0.5145	0.8702	0.9328
No log	6.5	182	0.8619	0.5220	0.8619	0.9284
No log	6.5714	184	0.9053	0.5379	0.9053	0.9515
No log	6.6429	186	1.0045	0.4871	1.0045	1.0022
No log	6.7143	188	1.1299	0.4717	1.1299	1.0630
No log	6.7857	190	1.1717	0.4709	1.1717	1.0825
No log	6.8571	192	1.0848	0.4790	1.0848	1.0415
No log	6.9286	194	0.9763	0.5374	0.9763	0.9881
No log	7.0	196	0.9658	0.5384	0.9658	0.9828
No log	7.0714	198	1.0374	0.4688	1.0374	1.0185
No log	7.1429	200	1.0540	0.4721	1.0540	1.0266
No log	7.2143	202	1.0425	0.4728	1.0425	1.0210
No log	7.2857	204	0.9725	0.4903	0.9725	0.9862
No log	7.3571	206	0.8801	0.5044	0.8801	0.9381
No log	7.4286	208	0.7969	0.5688	0.7969	0.8927
No log	7.5	210	0.7761	0.5503	0.7761	0.8810
No log	7.5714	212	0.7852	0.5688	0.7852	0.8861
No log	7.6429	214	0.8341	0.4897	0.8341	0.9133
No log	7.7143	216	0.9502	0.4719	0.9502	0.9748
No log	7.7857	218	1.0990	0.4323	1.0990	1.0483
No log	7.8571	220	1.2200	0.4092	1.2200	1.1045
No log	7.9286	222	1.2246	0.4053	1.2246	1.1066
No log	8.0	224	1.1372	0.4443	1.1372	1.0664
No log	8.0714	226	1.0269	0.4882	1.0269	1.0133
No log	8.1429	228	0.9140	0.5071	0.9140	0.9560
No log	8.2143	230	0.8544	0.5544	0.8544	0.9243
No log	8.2857	232	0.8475	0.5520	0.8475	0.9206
No log	8.3571	234	0.8654	0.5520	0.8654	0.9302
No log	8.4286	236	0.9031	0.5379	0.9031	0.9503
No log	8.5	238	0.9732	0.4888	0.9732	0.9865
No log	8.5714	240	1.0607	0.4739	1.0607	1.0299
No log	8.6429	242	1.0967	0.4575	1.0967	1.0472
No log	8.7143	244	1.0932	0.4575	1.0932	1.0455
No log	8.7857	246	1.0631	0.4581	1.0631	1.0311
No log	8.8571	248	1.0395	0.4581	1.0395	1.0196
No log	8.9286	250	1.0217	0.4578	1.0217	1.0108
No log	9.0	252	1.0002	0.4581	1.0002	1.0001
No log	9.0714	254	0.9693	0.4634	0.9693	0.9845
No log	9.1429	256	0.9565	0.4529	0.9565	0.9780
No log	9.2143	258	0.9610	0.4699	0.9610	0.9803
No log	9.2857	260	0.9600	0.4812	0.9600	0.9798
No log	9.3571	262	0.9716	0.4756	0.9716	0.9857
No log	9.4286	264	0.9775	0.4730	0.9775	0.9887
No log	9.5	266	0.9839	0.4730	0.9839	0.9919
No log	9.5714	268	0.9916	0.4730	0.9916	0.9958
No log	9.6429	270	0.9991	0.4730	0.9991	0.9995
No log	9.7143	272	0.9976	0.4730	0.9976	0.9988
No log	9.7857	274	0.9987	0.4730	0.9987	0.9993
No log	9.8571	276	0.9990	0.4730	0.9990	0.9995
No log	9.9286	278	1.0007	0.4730	1.0007	1.0003
No log	10.0	280	1.0013	0.4730	1.0013	1.0006

Framework versions

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