ArabicNewSplits6_FineTuningAraBERT_run1_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: 0.8879
• Qwk: 0.4381
• Mse: 0.8879
• Rmse: 0.9423

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	3.8976	-0.0187	3.8976	1.9742
No log	0.1538	4	2.0457	0.0146	2.0457	1.4303
No log	0.2308	6	1.2605	0.0495	1.2605	1.1227
No log	0.3077	8	1.0343	0.0290	1.0343	1.0170
No log	0.3846	10	0.7470	0.1025	0.7470	0.8643
No log	0.4615	12	0.7174	0.1869	0.7174	0.8470
No log	0.5385	14	0.7041	0.1869	0.7041	0.8391
No log	0.6154	16	0.6669	0.2378	0.6669	0.8167
No log	0.6923	18	0.8038	0.1375	0.8038	0.8965
No log	0.7692	20	0.8665	0.1154	0.8665	0.9309
No log	0.8462	22	0.7582	0.2217	0.7582	0.8707
No log	0.9231	24	0.6939	0.2333	0.6939	0.8330
No log	1.0	26	0.7913	0.2099	0.7913	0.8895
No log	1.0769	28	0.7352	0.2177	0.7352	0.8575
No log	1.1538	30	0.7316	0.2177	0.7316	0.8553
No log	1.2308	32	0.6228	0.3556	0.6228	0.7892
No log	1.3077	34	0.6172	0.3556	0.6172	0.7856
No log	1.3846	36	0.5939	0.3440	0.5939	0.7706
No log	1.4615	38	0.6068	0.3568	0.6068	0.7789
No log	1.5385	40	0.8717	0.3310	0.8717	0.9337
No log	1.6154	42	1.0898	0.2952	1.0898	1.0439
No log	1.6923	44	0.9287	0.3559	0.9287	0.9637
No log	1.7692	46	0.6899	0.5314	0.6899	0.8306
No log	1.8462	48	0.6332	0.5071	0.6332	0.7957
No log	1.9231	50	0.6396	0.5100	0.6396	0.7998
No log	2.0	52	0.7269	0.5239	0.7269	0.8526
No log	2.0769	54	0.7998	0.4520	0.7998	0.8943
No log	2.1538	56	0.7115	0.4924	0.7115	0.8435
No log	2.2308	58	0.5985	0.5215	0.5985	0.7737
No log	2.3077	60	0.6110	0.4780	0.6110	0.7817
No log	2.3846	62	0.6861	0.4439	0.6861	0.8283
No log	2.4615	64	0.6076	0.5047	0.6076	0.7795
No log	2.5385	66	0.5936	0.5246	0.5936	0.7705
No log	2.6154	68	0.6545	0.4710	0.6545	0.8090
No log	2.6923	70	0.6976	0.4593	0.6976	0.8352
No log	2.7692	72	0.6855	0.4594	0.6855	0.8279
No log	2.8462	74	0.7639	0.4782	0.7639	0.8740
No log	2.9231	76	0.8019	0.4659	0.8019	0.8955
No log	3.0	78	0.7501	0.5015	0.7501	0.8661
No log	3.0769	80	0.9154	0.3504	0.9154	0.9568
No log	3.1538	82	1.0148	0.3183	1.0148	1.0074
No log	3.2308	84	0.8817	0.3899	0.8817	0.9390
No log	3.3077	86	0.7810	0.4905	0.7810	0.8837
No log	3.3846	88	0.7917	0.4423	0.7917	0.8898
No log	3.4615	90	0.8686	0.4257	0.8686	0.9320
No log	3.5385	92	0.8859	0.3899	0.8859	0.9412
No log	3.6154	94	0.8384	0.4743	0.8384	0.9156
No log	3.6923	96	0.8137	0.4893	0.8137	0.9021
No log	3.7692	98	0.8404	0.5046	0.8404	0.9167
No log	3.8462	100	0.8094	0.5039	0.8094	0.8997
No log	3.9231	102	0.8179	0.4864	0.8179	0.9044
No log	4.0	104	0.8217	0.4761	0.8217	0.9065
No log	4.0769	106	0.7619	0.4940	0.7619	0.8729
No log	4.1538	108	0.8191	0.4381	0.8191	0.9050
No log	4.2308	110	0.9925	0.3876	0.9925	0.9962
No log	4.3077	112	1.0327	0.3611	1.0327	1.0162
No log	4.3846	114	0.8945	0.4344	0.8945	0.9458
No log	4.4615	116	0.7780	0.4650	0.7780	0.8821
No log	4.5385	118	0.8168	0.5028	0.8168	0.9038
No log	4.6154	120	0.8104	0.5368	0.8104	0.9002
No log	4.6923	122	0.7398	0.5057	0.7398	0.8601
No log	4.7692	124	0.7665	0.4345	0.7665	0.8755
No log	4.8462	126	0.8471	0.4404	0.8471	0.9204
No log	4.9231	128	0.8185	0.4458	0.8185	0.9047
No log	5.0	130	0.7748	0.4503	0.7748	0.8802
No log	5.0769	132	0.7560	0.4883	0.7560	0.8695
No log	5.1538	134	0.7513	0.4770	0.7513	0.8668
No log	5.2308	136	0.7721	0.5332	0.7721	0.8787
No log	5.3077	138	0.7947	0.5087	0.7947	0.8915
No log	5.3846	140	0.7975	0.5077	0.7975	0.8931
No log	5.4615	142	0.7780	0.4926	0.7780	0.8821
No log	5.5385	144	0.7773	0.4886	0.7773	0.8816
No log	5.6154	146	0.7712	0.5019	0.7712	0.8782
No log	5.6923	148	0.7584	0.5019	0.7584	0.8708
No log	5.7692	150	0.7430	0.4964	0.7430	0.8620
No log	5.8462	152	0.7428	0.4933	0.7428	0.8618
No log	5.9231	154	0.7592	0.5035	0.7592	0.8713
No log	6.0	156	0.7969	0.4776	0.7969	0.8927
No log	6.0769	158	0.8361	0.4816	0.8361	0.9144
No log	6.1538	160	0.8201	0.4776	0.8201	0.9056
No log	6.2308	162	0.7725	0.4809	0.7725	0.8789
No log	6.3077	164	0.7769	0.4653	0.7769	0.8814
No log	6.3846	166	0.8210	0.4824	0.8210	0.9061
No log	6.4615	168	0.8500	0.4641	0.8500	0.9220
No log	6.5385	170	0.8464	0.4728	0.8464	0.9200
No log	6.6154	172	0.8416	0.4334	0.8416	0.9174
No log	6.6923	174	0.8649	0.4574	0.8649	0.9300
No log	6.7692	176	0.8670	0.4468	0.8670	0.9311
No log	6.8462	178	0.8370	0.4557	0.8370	0.9149
No log	6.9231	180	0.8217	0.4434	0.8217	0.9065
No log	7.0	182	0.8271	0.4476	0.8271	0.9094
No log	7.0769	184	0.8496	0.4778	0.8496	0.9217
No log	7.1538	186	0.8542	0.4778	0.8542	0.9242
No log	7.2308	188	0.8474	0.4280	0.8474	0.9205
No log	7.3077	190	0.8547	0.4359	0.8547	0.9245
No log	7.3846	192	0.8666	0.4557	0.8666	0.9309
No log	7.4615	194	0.8828	0.4351	0.8828	0.9395
No log	7.5385	196	0.8999	0.4440	0.8999	0.9486
No log	7.6154	198	0.9100	0.5005	0.9100	0.9540
No log	7.6923	200	0.9113	0.4982	0.9113	0.9546
No log	7.7692	202	0.9047	0.4870	0.9047	0.9512
No log	7.8462	204	0.8887	0.4590	0.8887	0.9427
No log	7.9231	206	0.8802	0.4375	0.8802	0.9382
No log	8.0	208	0.8711	0.4262	0.8711	0.9333
No log	8.0769	210	0.8662	0.4262	0.8662	0.9307
No log	8.1538	212	0.8674	0.4144	0.8674	0.9313
No log	8.2308	214	0.8724	0.4280	0.8724	0.9340
No log	8.3077	216	0.8701	0.4144	0.8701	0.9328
No log	8.3846	218	0.8715	0.4145	0.8715	0.9335
No log	8.4615	220	0.8728	0.4262	0.8728	0.9342
No log	8.5385	222	0.8736	0.4262	0.8736	0.9347
No log	8.6154	224	0.8737	0.4383	0.8737	0.9347
No log	8.6923	226	0.8780	0.4314	0.8780	0.9370
No log	8.7692	228	0.8816	0.4382	0.8816	0.9390
No log	8.8462	230	0.8801	0.4383	0.8801	0.9381
No log	8.9231	232	0.8799	0.4381	0.8799	0.9380
No log	9.0	234	0.8820	0.4262	0.8820	0.9392
No log	9.0769	236	0.8869	0.4244	0.8869	0.9418
No log	9.1538	238	0.8932	0.4462	0.8932	0.9451
No log	9.2308	240	0.8964	0.4462	0.8964	0.9468
No log	9.3077	242	0.8951	0.4462	0.8951	0.9461
No log	9.3846	244	0.8934	0.4194	0.8934	0.9452
No log	9.4615	246	0.8924	0.4194	0.8924	0.9447
No log	9.5385	248	0.8920	0.4194	0.8920	0.9445
No log	9.6154	250	0.8919	0.4381	0.8919	0.9444
No log	9.6923	252	0.8911	0.4381	0.8911	0.9440
No log	9.7692	254	0.8895	0.4381	0.8895	0.9431
No log	9.8462	256	0.8884	0.4381	0.8884	0.9426
No log	9.9231	258	0.8881	0.4381	0.8881	0.9424
No log	10.0	260	0.8879	0.4381	0.8879	0.9423

Framework versions

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