ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run2_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: 0.8198
• Qwk: 0.7006
• Mse: 0.8198
• Rmse: 0.9054

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	2.2652	0.0137	2.2652	1.5050
No log	0.1538	4	1.6163	0.1566	1.6163	1.2713
No log	0.2308	6	1.3945	0.1254	1.3945	1.1809
No log	0.3077	8	1.4565	0.1888	1.4565	1.2069
No log	0.3846	10	1.6565	0.2991	1.6565	1.2871
No log	0.4615	12	1.6114	0.3243	1.6114	1.2694
No log	0.5385	14	1.4527	0.3459	1.4527	1.2053
No log	0.6154	16	1.2852	0.4003	1.2852	1.1337
No log	0.6923	18	1.2124	0.4351	1.2124	1.1011
No log	0.7692	20	1.0720	0.5021	1.0720	1.0354
No log	0.8462	22	1.0463	0.4980	1.0463	1.0229
No log	0.9231	24	1.1897	0.4764	1.1897	1.0907
No log	1.0	26	1.2282	0.5169	1.2282	1.1082
No log	1.0769	28	1.0711	0.4577	1.0711	1.0349
No log	1.1538	30	0.9812	0.4673	0.9812	0.9906
No log	1.2308	32	0.9606	0.4876	0.9606	0.9801
No log	1.3077	34	0.9229	0.5511	0.9229	0.9607
No log	1.3846	36	0.9404	0.5424	0.9404	0.9697
No log	1.4615	38	1.2152	0.5572	1.2152	1.1024
No log	1.5385	40	1.3574	0.4796	1.3574	1.1651
No log	1.6154	42	1.0580	0.5813	1.0580	1.0286
No log	1.6923	44	0.8003	0.5677	0.8003	0.8946
No log	1.7692	46	0.7931	0.5747	0.7931	0.8906
No log	1.8462	48	0.8231	0.5793	0.8231	0.9073
No log	1.9231	50	1.1137	0.6065	1.1137	1.0553
No log	2.0	52	1.6049	0.4888	1.6049	1.2668
No log	2.0769	54	1.5531	0.4920	1.5531	1.2462
No log	2.1538	56	1.1557	0.5433	1.1557	1.0750
No log	2.2308	58	1.0016	0.5551	1.0016	1.0008
No log	2.3077	60	0.8922	0.5700	0.8922	0.9446
No log	2.3846	62	0.9759	0.5855	0.9759	0.9879
No log	2.4615	64	1.1504	0.5463	1.1504	1.0726
No log	2.5385	66	1.0163	0.6012	1.0163	1.0081
No log	2.6154	68	0.8322	0.6422	0.8322	0.9122
No log	2.6923	70	0.7931	0.6026	0.7931	0.8906
No log	2.7692	72	0.7855	0.6459	0.7855	0.8863
No log	2.8462	74	0.9641	0.6619	0.9641	0.9819
No log	2.9231	76	1.5440	0.5338	1.5440	1.2426
No log	3.0	78	2.0050	0.4663	2.0050	1.4160
No log	3.0769	80	2.2480	0.4632	2.2480	1.4993
No log	3.1538	82	1.7344	0.5254	1.7344	1.3170
No log	3.2308	84	1.0269	0.6491	1.0269	1.0133
No log	3.3077	86	0.7980	0.6197	0.7980	0.8933
No log	3.3846	88	0.8083	0.6131	0.8083	0.8991
No log	3.4615	90	1.0350	0.6603	1.0350	1.0173
No log	3.5385	92	1.4542	0.5382	1.4542	1.2059
No log	3.6154	94	2.0283	0.4838	2.0283	1.4242
No log	3.6923	96	1.9307	0.4978	1.9307	1.3895
No log	3.7692	98	1.3111	0.5896	1.3111	1.1450
No log	3.8462	100	0.9109	0.6894	0.9109	0.9544
No log	3.9231	102	0.7944	0.6693	0.7944	0.8913
No log	4.0	104	0.8056	0.6562	0.8056	0.8976
No log	4.0769	106	0.9987	0.6706	0.9987	0.9994
No log	4.1538	108	1.5131	0.5545	1.5131	1.2301
No log	4.2308	110	1.7912	0.4955	1.7912	1.3384
No log	4.3077	112	1.6582	0.5304	1.6582	1.2877
No log	4.3846	114	1.1959	0.6036	1.1959	1.0936
No log	4.4615	116	0.9731	0.6714	0.9731	0.9865
No log	4.5385	118	0.8148	0.6418	0.8148	0.9026
No log	4.6154	120	0.8457	0.6756	0.8457	0.9196
No log	4.6923	122	1.0332	0.6555	1.0332	1.0164
No log	4.7692	124	1.2452	0.6149	1.2452	1.1159
No log	4.8462	126	1.3456	0.5963	1.3456	1.1600
No log	4.9231	128	1.1379	0.6321	1.1379	1.0667
No log	5.0	130	0.8593	0.7018	0.8593	0.9270
No log	5.0769	132	0.7279	0.6890	0.7279	0.8531
No log	5.1538	134	0.7014	0.6940	0.7014	0.8375
No log	5.2308	136	0.7688	0.7025	0.7688	0.8768
No log	5.3077	138	0.9949	0.6761	0.9949	0.9975
No log	5.3846	140	1.3154	0.5911	1.3154	1.1469
No log	5.4615	142	1.4137	0.5683	1.4137	1.1890
No log	5.5385	144	1.2975	0.5975	1.2975	1.1391
No log	5.6154	146	1.0627	0.6658	1.0627	1.0309
No log	5.6923	148	0.9294	0.6840	0.9294	0.9640
No log	5.7692	150	0.8592	0.7096	0.8592	0.9269
No log	5.8462	152	0.8960	0.6986	0.8960	0.9466
No log	5.9231	154	1.0189	0.6794	1.0189	1.0094
No log	6.0	156	0.9584	0.7028	0.9584	0.9790
No log	6.0769	158	0.9465	0.7101	0.9465	0.9729
No log	6.1538	160	1.0229	0.6826	1.0229	1.0114
No log	6.2308	162	1.1296	0.6794	1.1296	1.0628
No log	6.3077	164	1.0872	0.6688	1.0872	1.0427
No log	6.3846	166	1.0009	0.6781	1.0009	1.0004
No log	6.4615	168	0.8499	0.7041	0.8499	0.9219
No log	6.5385	170	0.8250	0.7057	0.8250	0.9083
No log	6.6154	172	0.9022	0.6939	0.9022	0.9498
No log	6.6923	174	0.9024	0.6874	0.9024	0.9500
No log	6.7692	176	0.8377	0.6967	0.8377	0.9153
No log	6.8462	178	0.8097	0.6932	0.8097	0.8998
No log	6.9231	180	0.7775	0.6958	0.7775	0.8817
No log	7.0	182	0.8264	0.6998	0.8264	0.9090
No log	7.0769	184	0.9569	0.6857	0.9569	0.9782
No log	7.1538	186	1.0728	0.6516	1.0728	1.0358
No log	7.2308	188	1.0451	0.6666	1.0451	1.0223
No log	7.3077	190	0.9723	0.6853	0.9723	0.9860
No log	7.3846	192	0.9571	0.6919	0.9571	0.9783
No log	7.4615	194	0.9042	0.7196	0.9042	0.9509
No log	7.5385	196	0.8648	0.7196	0.8648	0.9299
No log	7.6154	198	0.9046	0.7044	0.9046	0.9511
No log	7.6923	200	0.8776	0.7059	0.8776	0.9368
No log	7.7692	202	0.8307	0.6976	0.8307	0.9114
No log	7.8462	204	0.8472	0.6976	0.8472	0.9205
No log	7.9231	206	0.8907	0.6882	0.8907	0.9438
No log	8.0	208	0.9032	0.6916	0.9032	0.9504
No log	8.0769	210	0.9240	0.6688	0.9240	0.9612
No log	8.1538	212	0.8807	0.7011	0.8807	0.9384
No log	8.2308	214	0.8748	0.7011	0.8748	0.9353
No log	8.3077	216	0.8378	0.7003	0.8378	0.9153
No log	8.3846	218	0.8007	0.6967	0.8007	0.8948
No log	8.4615	220	0.7793	0.6967	0.7793	0.8828
No log	8.5385	222	0.8054	0.6967	0.8054	0.8974
No log	8.6154	224	0.8507	0.7007	0.8507	0.9223
No log	8.6923	226	0.9262	0.6739	0.9262	0.9624
No log	8.7692	228	0.9927	0.6583	0.9927	0.9963
No log	8.8462	230	0.9927	0.6632	0.9927	0.9963
No log	8.9231	232	0.9945	0.6570	0.9945	0.9973
No log	9.0	234	1.0106	0.6658	1.0106	1.0053
No log	9.0769	236	0.9814	0.6570	0.9814	0.9906
No log	9.1538	238	0.9328	0.6688	0.9328	0.9658
No log	9.2308	240	0.8984	0.6840	0.8984	0.9478
No log	9.3077	242	0.8832	0.6840	0.8832	0.9398
No log	9.3846	244	0.8637	0.7011	0.8637	0.9293
No log	9.4615	246	0.8442	0.6976	0.8442	0.9188
No log	9.5385	248	0.8305	0.6976	0.8305	0.9113
No log	9.6154	250	0.8170	0.6976	0.8170	0.9039
No log	9.6923	252	0.8100	0.7002	0.8100	0.9000
No log	9.7692	254	0.8143	0.7006	0.8143	0.9024
No log	9.8462	256	0.8176	0.7006	0.8176	0.9042
No log	9.9231	258	0.8189	0.7006	0.8189	0.9049
No log	10.0	260	0.8198	0.7006	0.8198	0.9054

Framework versions

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