ArabicNewSplits6_FineTuningAraBERT_run1_AugV5_k4_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: 1.0484
• Qwk: 0.6292
• Mse: 1.0484
• Rmse: 1.0239

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	0.1111	2	2.4628	0.0098	2.4628	1.5693
No log	0.2222	4	1.8976	0.0604	1.8976	1.3775
No log	0.3333	6	1.2376	0.2634	1.2376	1.1125
No log	0.4444	8	1.5269	0.1001	1.5269	1.2357
No log	0.5556	10	1.5187	0.1475	1.5187	1.2323
No log	0.6667	12	1.4988	0.1628	1.4988	1.2243
No log	0.7778	14	1.4460	0.1475	1.4460	1.2025
No log	0.8889	16	1.4579	0.1622	1.4579	1.2075
No log	1.0	18	1.4802	0.2356	1.4802	1.2166
No log	1.1111	20	1.4576	0.2067	1.4576	1.2073
No log	1.2222	22	1.5428	0.3013	1.5428	1.2421
No log	1.3333	24	1.5384	0.3499	1.5384	1.2403
No log	1.4444	26	1.4382	0.2751	1.4382	1.1993
No log	1.5556	28	1.3310	0.2232	1.3310	1.1537
No log	1.6667	30	1.3008	0.2577	1.3008	1.1405
No log	1.7778	32	1.2449	0.3070	1.2449	1.1157
No log	1.8889	34	1.3346	0.3893	1.3346	1.1552
No log	2.0	36	1.4464	0.3768	1.4464	1.2027
No log	2.1111	38	1.3382	0.3921	1.3382	1.1568
No log	2.2222	40	1.3136	0.3918	1.3136	1.1461
No log	2.3333	42	1.3144	0.3886	1.3144	1.1465
No log	2.4444	44	1.1936	0.3986	1.1936	1.0925
No log	2.5556	46	1.0991	0.3821	1.0991	1.0484
No log	2.6667	48	1.0721	0.3845	1.0721	1.0354
No log	2.7778	50	1.1370	0.4546	1.1370	1.0663
No log	2.8889	52	1.5439	0.4071	1.5439	1.2425
No log	3.0	54	1.9311	0.3027	1.9311	1.3896
No log	3.1111	56	2.0436	0.3027	2.0436	1.4296
No log	3.2222	58	1.9746	0.3125	1.9746	1.4052
No log	3.3333	60	1.7417	0.3455	1.7417	1.3197
No log	3.4444	62	1.3554	0.4822	1.3554	1.1642
No log	3.5556	64	1.0019	0.4862	1.0019	1.0009
No log	3.6667	66	1.0022	0.5202	1.0022	1.0011
No log	3.7778	68	1.1359	0.4179	1.1359	1.0658
No log	3.8889	70	1.1014	0.4425	1.1014	1.0495
No log	4.0	72	0.9910	0.4955	0.9910	0.9955
No log	4.1111	74	0.9580	0.4673	0.9580	0.9788
No log	4.2222	76	1.0499	0.4859	1.0499	1.0246
No log	4.3333	78	1.1063	0.5216	1.1063	1.0518
No log	4.4444	80	1.1740	0.4903	1.1740	1.0835
No log	4.5556	82	1.1157	0.5211	1.1157	1.0563
No log	4.6667	84	1.0306	0.4843	1.0306	1.0152
No log	4.7778	86	0.9946	0.4768	0.9946	0.9973
No log	4.8889	88	0.9239	0.5104	0.9239	0.9612
No log	5.0	90	0.8815	0.5539	0.8815	0.9389
No log	5.1111	92	0.8669	0.5539	0.8669	0.9311
No log	5.2222	94	0.8576	0.5834	0.8576	0.9261
No log	5.3333	96	0.8626	0.5400	0.8626	0.9287
No log	5.4444	98	0.9217	0.5559	0.9217	0.9600
No log	5.5556	100	1.0406	0.5375	1.0406	1.0201
No log	5.6667	102	1.2291	0.5073	1.2291	1.1086
No log	5.7778	104	1.3004	0.5365	1.3004	1.1404
No log	5.8889	106	1.2345	0.5565	1.2345	1.1111
No log	6.0	108	1.0657	0.5696	1.0657	1.0323
No log	6.1111	110	0.8954	0.6231	0.8954	0.9463
No log	6.2222	112	0.8589	0.6557	0.8589	0.9268
No log	6.3333	114	0.8817	0.6449	0.8817	0.9390
No log	6.4444	116	0.9658	0.6110	0.9658	0.9827
No log	6.5556	118	1.0670	0.5787	1.0670	1.0329
No log	6.6667	120	1.1088	0.5677	1.1088	1.0530
No log	6.7778	122	1.1256	0.5722	1.1256	1.0609
No log	6.8889	124	1.1157	0.5755	1.1157	1.0563
No log	7.0	126	1.1375	0.5851	1.1375	1.0665
No log	7.1111	128	1.1368	0.5818	1.1368	1.0662
No log	7.2222	130	1.0391	0.6001	1.0391	1.0194
No log	7.3333	132	0.9319	0.6211	0.9319	0.9654
No log	7.4444	134	0.8448	0.6474	0.8448	0.9192
No log	7.5556	136	0.7929	0.6684	0.7929	0.8904
No log	7.6667	138	0.8029	0.6684	0.8029	0.8960
No log	7.7778	140	0.8788	0.6530	0.8788	0.9374
No log	7.8889	142	1.0199	0.6219	1.0199	1.0099
No log	8.0	144	1.2208	0.5804	1.2208	1.1049
No log	8.1111	146	1.3513	0.5811	1.3513	1.1625
No log	8.2222	148	1.3500	0.5811	1.3500	1.1619
No log	8.3333	150	1.2520	0.6172	1.2520	1.1189
No log	8.4444	152	1.1238	0.6178	1.1238	1.0601
No log	8.5556	154	1.0360	0.6292	1.0360	1.0178
No log	8.6667	156	0.9890	0.6202	0.9890	0.9945
No log	8.7778	158	0.9237	0.6282	0.9237	0.9611
No log	8.8889	160	0.8799	0.6542	0.8799	0.9380
No log	9.0	162	0.8697	0.6634	0.8697	0.9326
No log	9.1111	164	0.8895	0.6627	0.8895	0.9431
No log	9.2222	166	0.9214	0.6581	0.9214	0.9599
No log	9.3333	168	0.9472	0.6287	0.9472	0.9732
No log	9.4444	170	0.9784	0.6234	0.9784	0.9891
No log	9.5556	172	0.9991	0.6234	0.9991	0.9995
No log	9.6667	174	1.0121	0.6234	1.0121	1.0060
No log	9.7778	176	1.0286	0.6292	1.0286	1.0142
No log	9.8889	178	1.0424	0.6292	1.0424	1.0210
No log	10.0	180	1.0484	0.6292	1.0484	1.0239

Framework versions

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