Arabic_FineTuningAraBERT_AugV0_k3_task1_organization_fold1

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: 0.5252
• Qwk: 0.6831
• Mse: 0.5252
• Rmse: 0.7247

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	4.7414	0.0094	4.7414	2.1775
No log	0.1538	4	3.6945	-0.0630	3.6945	1.9221
No log	0.2308	6	2.0868	0.0401	2.0868	1.4446
No log	0.3077	8	1.2520	0.3077	1.2520	1.1189
No log	0.3846	10	1.1637	0.4815	1.1637	1.0788
No log	0.4615	12	0.7045	0.3000	0.7045	0.8393
No log	0.5385	14	0.8215	0.3568	0.8215	0.9064
No log	0.6154	16	0.8136	0.1529	0.8136	0.9020
No log	0.6923	18	0.6856	0.25	0.6856	0.8280
No log	0.7692	20	0.5752	0.5969	0.5752	0.7584
No log	0.8462	22	0.5351	0.4615	0.5351	0.7315
No log	0.9231	24	0.5808	0.5532	0.5808	0.7621
No log	1.0	26	0.4474	0.58	0.4474	0.6689
No log	1.0769	28	0.4311	0.7107	0.4311	0.6566
No log	1.1538	30	0.4061	0.6778	0.4061	0.6372
No log	1.2308	32	0.4149	0.7529	0.4149	0.6441
No log	1.3077	34	0.3937	0.7529	0.3937	0.6274
No log	1.3846	36	0.3913	0.6131	0.3913	0.6256
No log	1.4615	38	0.3740	0.6244	0.3740	0.6116
No log	1.5385	40	0.3548	0.6392	0.3548	0.5956
No log	1.6154	42	0.3783	0.5926	0.3783	0.6151
No log	1.6923	44	0.3637	0.6419	0.3637	0.6030
No log	1.7692	46	0.3745	0.6903	0.3745	0.6120
No log	1.8462	48	0.3518	0.6547	0.3518	0.5932
No log	1.9231	50	0.3771	0.6351	0.3771	0.6141
No log	2.0	52	0.4806	0.5532	0.4806	0.6933
No log	2.0769	54	0.4787	0.6	0.4787	0.6919
No log	2.1538	56	0.4871	0.6379	0.4871	0.6979
No log	2.2308	58	0.4494	0.75	0.4494	0.6704
No log	2.3077	60	0.3479	0.7879	0.3479	0.5898
No log	2.3846	62	0.3272	0.7812	0.3272	0.5720
No log	2.4615	64	0.3431	0.7107	0.3431	0.5857
No log	2.5385	66	0.3516	0.7107	0.3516	0.5930
No log	2.6154	68	0.3634	0.7510	0.3634	0.6028
No log	2.6923	70	0.4125	0.7879	0.4125	0.6422
No log	2.7692	72	0.4621	0.7138	0.4621	0.6798
No log	2.8462	74	0.4865	0.6883	0.4865	0.6975
No log	2.9231	76	0.4840	0.6883	0.4840	0.6957
No log	3.0	78	0.4795	0.7138	0.4795	0.6925
No log	3.0769	80	0.4424	0.7287	0.4424	0.6651
No log	3.1538	82	0.5221	0.7445	0.5221	0.7226
No log	3.2308	84	0.5390	0.7445	0.5390	0.7342
No log	3.3077	86	0.5405	0.7605	0.5405	0.7352
No log	3.3846	88	0.4075	0.6912	0.4075	0.6384
No log	3.4615	90	0.3764	0.72	0.3764	0.6135
No log	3.5385	92	0.3895	0.6695	0.3895	0.6241
No log	3.6154	94	0.4357	0.6957	0.4357	0.6601
No log	3.6923	96	0.4902	0.6957	0.4902	0.7001
No log	3.7692	98	0.5830	0.6723	0.5830	0.7636
No log	3.8462	100	0.6878	0.5817	0.6878	0.8293
No log	3.9231	102	0.7044	0.5817	0.7044	0.8393
No log	4.0	104	0.5744	0.6585	0.5744	0.7579
No log	4.0769	106	0.4264	0.6805	0.4264	0.6530
No log	4.1538	108	0.3291	0.6778	0.3291	0.5737
No log	4.2308	110	0.3221	0.8108	0.3221	0.5675
No log	4.3077	112	0.3157	0.8158	0.3157	0.5618
No log	4.3846	114	0.3478	0.7756	0.3478	0.5898
No log	4.4615	116	0.4313	0.7729	0.4313	0.6567
No log	4.5385	118	0.6079	0.6975	0.6079	0.7797
No log	4.6154	120	0.6892	0.6478	0.6892	0.8302
No log	4.6923	122	0.6545	0.6416	0.6545	0.8090
No log	4.7692	124	0.5929	0.6693	0.5929	0.7700
No log	4.8462	126	0.4709	0.7308	0.4709	0.6862
No log	4.9231	128	0.4206	0.7072	0.4206	0.6486
No log	5.0	130	0.4094	0.7470	0.4094	0.6398
No log	5.0769	132	0.4158	0.7470	0.4158	0.6448
No log	5.1538	134	0.4594	0.6831	0.4594	0.6778
No log	5.2308	136	0.4854	0.6693	0.4854	0.6967
No log	5.3077	138	0.4632	0.6983	0.4632	0.6806
No log	5.3846	140	0.4226	0.6983	0.4226	0.6501
No log	5.4615	142	0.3758	0.6875	0.3758	0.6130
No log	5.5385	144	0.3668	0.6957	0.3668	0.6056
No log	5.6154	146	0.3792	0.6805	0.3792	0.6158
No log	5.6923	148	0.4151	0.6983	0.4151	0.6443
No log	5.7692	150	0.4178	0.7605	0.4178	0.6464
No log	5.8462	152	0.3982	0.7552	0.3982	0.6310
No log	5.9231	154	0.3888	0.7390	0.3888	0.6235
No log	6.0	156	0.3649	0.8	0.3649	0.6041
No log	6.0769	158	0.3891	0.7853	0.3891	0.6237
No log	6.1538	160	0.3996	0.7853	0.3996	0.6321
No log	6.2308	162	0.4432	0.7552	0.4432	0.6657
No log	6.3077	164	0.5074	0.6934	0.5074	0.7123
No log	6.3846	166	0.5805	0.6038	0.5805	0.7619
No log	6.4615	168	0.6236	0.6038	0.6236	0.7897
No log	6.5385	170	0.5972	0.6038	0.5972	0.7728
No log	6.6154	172	0.5400	0.6459	0.5400	0.7348
No log	6.6923	174	0.4601	0.6805	0.4601	0.6783
No log	6.7692	176	0.4254	0.6805	0.4254	0.6523
No log	6.8462	178	0.4306	0.6805	0.4306	0.6562
No log	6.9231	180	0.4642	0.6908	0.4642	0.6813
No log	7.0	182	0.4626	0.7298	0.4626	0.6802
No log	7.0769	184	0.5103	0.7298	0.5103	0.7144
No log	7.1538	186	0.5553	0.6729	0.5553	0.7452
No log	7.2308	188	0.5391	0.6729	0.5391	0.7343
No log	7.3077	190	0.4822	0.7298	0.4822	0.6944
No log	7.3846	192	0.4320	0.7308	0.4320	0.6573
No log	7.4615	194	0.4199	0.7059	0.4199	0.6480
No log	7.5385	196	0.4131	0.6805	0.4131	0.6427
No log	7.6154	198	0.4304	0.6805	0.4304	0.6560
No log	7.6923	200	0.4307	0.6805	0.4307	0.6563
No log	7.7692	202	0.4450	0.6805	0.4450	0.6671
No log	7.8462	204	0.4610	0.6667	0.4610	0.6790
No log	7.9231	206	0.4839	0.6667	0.4839	0.6956
No log	8.0	208	0.5376	0.6693	0.5376	0.7332
No log	8.0769	210	0.5565	0.6693	0.5565	0.7460
No log	8.1538	212	0.5628	0.6693	0.5628	0.7502
No log	8.2308	214	0.5518	0.6693	0.5518	0.7428
No log	8.3077	216	0.5127	0.7154	0.5127	0.7160
No log	8.3846	218	0.4803	0.6715	0.4803	0.6930
No log	8.4615	220	0.4713	0.6715	0.4713	0.6865
No log	8.5385	222	0.4447	0.7279	0.4447	0.6669
No log	8.6154	224	0.4316	0.7279	0.4316	0.6569
No log	8.6923	226	0.4265	0.7287	0.4265	0.6530
No log	8.7692	228	0.4349	0.6805	0.4349	0.6595
No log	8.8462	230	0.4617	0.6715	0.4617	0.6795
No log	8.9231	232	0.4827	0.7159	0.4827	0.6948
No log	9.0	234	0.5241	0.6416	0.5241	0.7239
No log	9.0769	236	0.5699	0.6316	0.5699	0.7549
No log	9.1538	238	0.5924	0.6316	0.5924	0.7697
No log	9.2308	240	0.5938	0.6316	0.5938	0.7706
No log	9.3077	242	0.5819	0.6316	0.5819	0.7628
No log	9.3846	244	0.5639	0.6316	0.5639	0.7510
No log	9.4615	246	0.5558	0.6316	0.5558	0.7455
No log	9.5385	248	0.5487	0.6316	0.5487	0.7407
No log	9.6154	250	0.5415	0.6693	0.5415	0.7358
No log	9.6923	252	0.5343	0.6831	0.5343	0.7309
No log	9.7692	254	0.5288	0.6831	0.5288	0.7272
No log	9.8462	256	0.5262	0.6831	0.5262	0.7254
No log	9.9231	258	0.5255	0.6831	0.5255	0.7249
No log	10.0	260	0.5252	0.6831	0.5252	0.7247

Framework versions

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