ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k6_task5_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: 1.0128
• Qwk: 0.6327
• Mse: 1.0128
• Rmse: 1.0064

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	0.0769	2	2.4316	0.0041	2.4316	1.5594
No log	0.1538	4	1.6386	0.1382	1.6386	1.2801
No log	0.2308	6	1.4122	0.1697	1.4122	1.1884
No log	0.3077	8	1.3835	0.1209	1.3835	1.1762
No log	0.3846	10	1.3962	0.1475	1.3962	1.1816
No log	0.4615	12	1.4142	0.2003	1.4142	1.1892
No log	0.5385	14	1.6130	0.3563	1.6130	1.2700
No log	0.6154	16	1.6694	0.3670	1.6694	1.2921
No log	0.6923	18	1.4993	0.3755	1.4993	1.2245
No log	0.7692	20	1.4421	0.3746	1.4421	1.2009
No log	0.8462	22	1.4576	0.3858	1.4576	1.2073
No log	0.9231	24	1.4050	0.3858	1.4050	1.1853
No log	1.0	26	1.3027	0.3416	1.3027	1.1413
No log	1.0769	28	1.2800	0.3179	1.2800	1.1314
No log	1.1538	30	1.2155	0.1749	1.2155	1.1025
No log	1.2308	32	1.1432	0.1743	1.1432	1.0692
No log	1.3077	34	1.0990	0.3404	1.0990	1.0484
No log	1.3846	36	1.1493	0.4005	1.1493	1.0720
No log	1.4615	38	1.3038	0.4292	1.3038	1.1418
No log	1.5385	40	1.4417	0.3901	1.4417	1.2007
No log	1.6154	42	1.4725	0.4052	1.4725	1.2135
No log	1.6923	44	1.5636	0.3916	1.5636	1.2504
No log	1.7692	46	1.4439	0.4386	1.4439	1.2016
No log	1.8462	48	1.1928	0.4462	1.1928	1.0922
No log	1.9231	50	1.0947	0.4646	1.0947	1.0463
No log	2.0	52	1.1390	0.4174	1.1390	1.0673
No log	2.0769	54	1.1014	0.4464	1.1014	1.0495
No log	2.1538	56	1.0671	0.4266	1.0671	1.0330
No log	2.2308	58	1.1447	0.4441	1.1447	1.0699
No log	2.3077	60	1.3027	0.4722	1.3027	1.1414
No log	2.3846	62	1.4577	0.4247	1.4577	1.2074
No log	2.4615	64	1.5373	0.4132	1.5373	1.2399
No log	2.5385	66	1.5261	0.4371	1.5261	1.2353
No log	2.6154	68	1.3875	0.4466	1.3875	1.1779
No log	2.6923	70	1.2531	0.4644	1.2531	1.1194
No log	2.7692	72	1.1684	0.4755	1.1684	1.0809
No log	2.8462	74	1.1816	0.4795	1.1816	1.0870
No log	2.9231	76	1.1790	0.5034	1.1790	1.0858
No log	3.0	78	1.1438	0.5403	1.1438	1.0695
No log	3.0769	80	1.1916	0.5466	1.1916	1.0916
No log	3.1538	82	1.2969	0.5337	1.2969	1.1388
No log	3.2308	84	1.3246	0.5176	1.3246	1.1509
No log	3.3077	86	1.2143	0.5501	1.2143	1.1020
No log	3.3846	88	1.0188	0.5973	1.0188	1.0093
No log	3.4615	90	0.9379	0.6486	0.9379	0.9685
No log	3.5385	92	0.9202	0.6486	0.9202	0.9593
No log	3.6154	94	0.9231	0.6278	0.9231	0.9608
No log	3.6923	96	0.9515	0.6006	0.9515	0.9755
No log	3.7692	98	1.0596	0.5874	1.0596	1.0293
No log	3.8462	100	1.2118	0.5930	1.2118	1.1008
No log	3.9231	102	1.3792	0.5186	1.3792	1.1744
No log	4.0	104	1.3356	0.5351	1.3356	1.1557
No log	4.0769	106	1.1046	0.5616	1.1046	1.0510
No log	4.1538	108	0.9980	0.5940	0.9980	0.9990
No log	4.2308	110	0.9454	0.6175	0.9454	0.9723
No log	4.3077	112	0.8911	0.6390	0.8911	0.9440
No log	4.3846	114	0.9335	0.6022	0.9335	0.9662
No log	4.4615	116	1.1027	0.5606	1.1027	1.0501
No log	4.5385	118	1.3353	0.5391	1.3353	1.1556
No log	4.6154	120	1.3926	0.5450	1.3926	1.1801
No log	4.6923	122	1.3121	0.5578	1.3121	1.1455
No log	4.7692	124	1.1453	0.5568	1.1453	1.0702
No log	4.8462	126	0.9765	0.5925	0.9765	0.9882
No log	4.9231	128	0.9509	0.6004	0.9509	0.9751
No log	5.0	130	0.9867	0.6075	0.9867	0.9933
No log	5.0769	132	1.0172	0.6135	1.0172	1.0086
No log	5.1538	134	1.1219	0.5852	1.1219	1.0592
No log	5.2308	136	1.1289	0.5887	1.1289	1.0625
No log	5.3077	138	1.1076	0.5790	1.1076	1.0524
No log	5.3846	140	1.1470	0.5702	1.1470	1.0710
No log	5.4615	142	1.2011	0.5459	1.2011	1.0960
No log	5.5385	144	1.0857	0.5472	1.0857	1.0420
No log	5.6154	146	0.9591	0.6250	0.9591	0.9793
No log	5.6923	148	0.8363	0.6839	0.8363	0.9145
No log	5.7692	150	0.7967	0.7020	0.7967	0.8926
No log	5.8462	152	0.7984	0.6785	0.7984	0.8935
No log	5.9231	154	0.8651	0.6659	0.8651	0.9301
No log	6.0	156	0.9803	0.6172	0.9803	0.9901
No log	6.0769	158	1.1224	0.5891	1.1224	1.0595
No log	6.1538	160	1.2223	0.5695	1.2223	1.1056
No log	6.2308	162	1.2212	0.5666	1.2212	1.1051
No log	6.3077	164	1.1333	0.5715	1.1333	1.0646
No log	6.3846	166	1.0271	0.5831	1.0271	1.0134
No log	6.4615	168	0.9429	0.6346	0.9429	0.9710
No log	6.5385	170	0.9061	0.6469	0.9061	0.9519
No log	6.6154	172	0.8804	0.6478	0.8804	0.9383
No log	6.6923	174	0.8967	0.6478	0.8967	0.9469
No log	6.7692	176	0.9457	0.6411	0.9457	0.9724
No log	6.8462	178	1.0117	0.6050	1.0117	1.0058
No log	6.9231	180	1.0398	0.5862	1.0398	1.0197
No log	7.0	182	1.0724	0.5787	1.0724	1.0356
No log	7.0769	184	1.0482	0.5875	1.0482	1.0238
No log	7.1538	186	1.0412	0.5875	1.0412	1.0204
No log	7.2308	188	1.0579	0.5893	1.0579	1.0285
No log	7.3077	190	1.0680	0.5893	1.0680	1.0334
No log	7.3846	192	1.0763	0.5893	1.0763	1.0374
No log	7.4615	194	1.0150	0.6261	1.0150	1.0075
No log	7.5385	196	0.9425	0.6357	0.9425	0.9708
No log	7.6154	198	0.8845	0.6308	0.8845	0.9405
No log	7.6923	200	0.8692	0.6294	0.8692	0.9323
No log	7.7692	202	0.8822	0.6410	0.8822	0.9393
No log	7.8462	204	0.9326	0.6392	0.9326	0.9657
No log	7.9231	206	0.9712	0.6304	0.9712	0.9855
No log	8.0	208	1.0156	0.5937	1.0156	1.0078
No log	8.0769	210	1.0122	0.6120	1.0122	1.0061
No log	8.1538	212	0.9598	0.6476	0.9598	0.9797
No log	8.2308	214	0.9347	0.6595	0.9347	0.9668
No log	8.3077	216	0.9341	0.6514	0.9341	0.9665
No log	8.3846	218	0.9469	0.6514	0.9469	0.9731
No log	8.4615	220	0.9425	0.6508	0.9425	0.9708
No log	8.5385	222	0.9657	0.6465	0.9657	0.9827
No log	8.6154	224	1.0055	0.5964	1.0055	1.0028
No log	8.6923	226	1.0096	0.6147	1.0096	1.0048
No log	8.7692	228	0.9859	0.6252	0.9859	0.9929
No log	8.8462	230	0.9726	0.6252	0.9726	0.9862
No log	8.9231	232	0.9662	0.6295	0.9662	0.9830
No log	9.0	234	0.9676	0.6295	0.9676	0.9837
No log	9.0769	236	0.9766	0.6246	0.9766	0.9882
No log	9.1538	238	0.9911	0.6205	0.9911	0.9955
No log	9.2308	240	0.9938	0.6176	0.9938	0.9969
No log	9.3077	242	0.9845	0.6308	0.9845	0.9922
No log	9.3846	244	0.9872	0.6266	0.9872	0.9936
No log	9.4615	246	0.9904	0.6266	0.9904	0.9952
No log	9.5385	248	0.9932	0.6266	0.9932	0.9966
No log	9.6154	250	1.0021	0.6266	1.0021	1.0010
No log	9.6923	252	1.0106	0.6327	1.0106	1.0053
No log	9.7692	254	1.0140	0.6327	1.0140	1.0070
No log	9.8462	256	1.0135	0.6327	1.0135	1.0067
No log	9.9231	258	1.0133	0.6327	1.0133	1.0066
No log	10.0	260	1.0128	0.6327	1.0128	1.0064

Framework versions

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