ArabicNewSplits5_FineTuningAraBERT_run1_AugV5_k3_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: 1.1568
• Qwk: 0.5705
• Mse: 1.1568
• Rmse: 1.0756

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	0.1176	2	2.1255	-0.0173	2.1255	1.4579
No log	0.2353	4	1.6254	0.1225	1.6254	1.2749
No log	0.3529	6	1.4914	0.1209	1.4914	1.2212
No log	0.4706	8	1.4281	0.1415	1.4281	1.1950
No log	0.5882	10	1.3824	0.1423	1.3824	1.1758
No log	0.7059	12	1.3616	0.1093	1.3616	1.1669
No log	0.8235	14	1.3803	0.1475	1.3803	1.1749
No log	0.9412	16	1.3817	0.1968	1.3817	1.1755
No log	1.0588	18	1.3513	0.1968	1.3513	1.1625
No log	1.1765	20	1.3298	0.1475	1.3298	1.1532
No log	1.2941	22	1.3404	0.1700	1.3404	1.1578
No log	1.4118	24	1.3307	0.2401	1.3307	1.1536
No log	1.5294	26	1.2660	0.2539	1.2660	1.1252
No log	1.6471	28	1.2154	0.2565	1.2154	1.1024
No log	1.7647	30	1.1693	0.3077	1.1693	1.0814
No log	1.8824	32	1.1636	0.3591	1.1636	1.0787
No log	2.0	34	1.1376	0.3764	1.1376	1.0666
No log	2.1176	36	1.1240	0.3801	1.1240	1.0602
No log	2.2353	38	1.1030	0.3872	1.1030	1.0502
No log	2.3529	40	1.1109	0.3313	1.1109	1.0540
No log	2.4706	42	1.1013	0.3142	1.1013	1.0494
No log	2.5882	44	1.0820	0.3259	1.0820	1.0402
No log	2.7059	46	1.0588	0.3411	1.0588	1.0290
No log	2.8235	48	1.0350	0.3546	1.0350	1.0173
No log	2.9412	50	1.0169	0.4318	1.0169	1.0084
No log	3.0588	52	1.0301	0.4990	1.0301	1.0149
No log	3.1765	54	1.0157	0.5033	1.0157	1.0078
No log	3.2941	56	0.9702	0.5150	0.9702	0.9850
No log	3.4118	58	0.9451	0.4624	0.9451	0.9722
No log	3.5294	60	0.9435	0.5108	0.9435	0.9713
No log	3.6471	62	0.9992	0.5786	0.9992	0.9996
No log	3.7647	64	1.0759	0.5354	1.0759	1.0372
No log	3.8824	66	1.1911	0.4913	1.1911	1.0914
No log	4.0	68	1.2722	0.4933	1.2722	1.1279
No log	4.1176	70	1.3234	0.4833	1.3234	1.1504
No log	4.2353	72	1.2167	0.5370	1.2167	1.1030
No log	4.3529	74	1.1915	0.5557	1.1915	1.0916
No log	4.4706	76	1.0835	0.5341	1.0835	1.0409
No log	4.5882	78	0.9906	0.5391	0.9906	0.9953
No log	4.7059	80	0.9552	0.5656	0.9552	0.9774
No log	4.8235	82	0.9968	0.5562	0.9968	0.9984
No log	4.9412	84	1.0622	0.5480	1.0622	1.0307
No log	5.0588	86	1.1321	0.5710	1.1321	1.0640
No log	5.1765	88	1.1553	0.5592	1.1553	1.0749
No log	5.2941	90	1.1985	0.5389	1.1985	1.0948
No log	5.4118	92	1.1636	0.5840	1.1636	1.0787
No log	5.5294	94	1.1425	0.5922	1.1425	1.0689
No log	5.6471	96	1.1819	0.5188	1.1819	1.0871
No log	5.7647	98	1.1689	0.5526	1.1689	1.0812
No log	5.8824	100	1.2249	0.5478	1.2249	1.1067
No log	6.0	102	1.2373	0.5527	1.2373	1.1124
No log	6.1176	104	1.1858	0.5725	1.1858	1.0889
No log	6.2353	106	1.1439	0.5945	1.1439	1.0695
No log	6.3529	108	1.1174	0.6083	1.1174	1.0571
No log	6.4706	110	1.1468	0.5857	1.1468	1.0709
No log	6.5882	112	1.1475	0.5947	1.1475	1.0712
No log	6.7059	114	1.0982	0.6052	1.0982	1.0479
No log	6.8235	116	1.0471	0.6331	1.0471	1.0233
No log	6.9412	118	0.9854	0.6394	0.9854	0.9927
No log	7.0588	120	0.9646	0.6548	0.9646	0.9821
No log	7.1765	122	1.0049	0.6408	1.0049	1.0025
No log	7.2941	124	1.0999	0.6314	1.0999	1.0488
No log	7.4118	126	1.1766	0.5861	1.1766	1.0847
No log	7.5294	128	1.1922	0.5952	1.1922	1.0919
No log	7.6471	130	1.1417	0.6041	1.1417	1.0685
No log	7.7647	132	1.0713	0.6289	1.0713	1.0351
No log	7.8824	134	1.0136	0.6518	1.0136	1.0068
No log	8.0	136	0.9813	0.6390	0.9813	0.9906
No log	8.1176	138	0.9815	0.6351	0.9815	0.9907
No log	8.2353	140	1.0167	0.6310	1.0167	1.0083
No log	8.3529	142	1.0677	0.6174	1.0677	1.0333
No log	8.4706	144	1.1230	0.5866	1.1230	1.0597
No log	8.5882	146	1.2015	0.5591	1.2015	1.0961
No log	8.7059	148	1.2590	0.5534	1.2590	1.1221
No log	8.8235	150	1.2746	0.5556	1.2746	1.1290
No log	8.9412	152	1.2668	0.5556	1.2668	1.1255
No log	9.0588	154	1.2578	0.5565	1.2578	1.1215
No log	9.1765	156	1.2271	0.5645	1.2271	1.1077
No log	9.2941	158	1.2038	0.5645	1.2038	1.0972
No log	9.4118	160	1.1923	0.5623	1.1923	1.0919
No log	9.5294	162	1.1844	0.5623	1.1844	1.0883
No log	9.6471	164	1.1789	0.5623	1.1789	1.0858
No log	9.7647	166	1.1702	0.5705	1.1702	1.0817
No log	9.8824	168	1.1602	0.5705	1.1602	1.0771
No log	10.0	170	1.1568	0.5705	1.1568	1.0756

Framework versions

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