ArabicNewSplits_FineTuningAraBERT_AugV5_k4_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: 1.6558
• Qwk: 0.2520
• Mse: 1.6558
• Rmse: 1.2868

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	0.1	2	4.4441	-0.0412	4.4441	2.1081
No log	0.2	4	2.5659	0.0425	2.5659	1.6018
No log	0.3	6	1.3937	0.2215	1.3937	1.1805
No log	0.4	8	1.1796	0.0791	1.1796	1.0861
No log	0.5	10	1.1374	0.2234	1.1374	1.0665
No log	0.6	12	1.4108	0.0305	1.4108	1.1878
No log	0.7	14	1.2572	0.0927	1.2572	1.1213
No log	0.8	16	1.1438	0.0139	1.1438	1.0695
No log	0.9	18	1.2005	0.0	1.2005	1.0957
No log	1.0	20	1.2299	0.0	1.2299	1.1090
No log	1.1	22	1.2269	0.0	1.2269	1.1077
No log	1.2	24	1.1291	0.0757	1.1291	1.0626
No log	1.3	26	1.0791	0.0757	1.0791	1.0388
No log	1.4	28	1.0523	0.2419	1.0523	1.0258
No log	1.5	30	1.0508	0.3502	1.0508	1.0251
No log	1.6	32	1.1134	0.1793	1.1134	1.0552
No log	1.7	34	1.1497	0.2176	1.1497	1.0722
No log	1.8	36	1.1651	0.1937	1.1651	1.0794
No log	1.9	38	1.1567	0.2241	1.1567	1.0755
No log	2.0	40	1.1134	0.2149	1.1134	1.0552
No log	2.1	42	1.1095	0.2167	1.1095	1.0534
No log	2.2	44	1.1009	0.2149	1.1009	1.0492
No log	2.3	46	1.1866	0.1475	1.1866	1.0893
No log	2.4	48	1.3197	0.0809	1.3197	1.1488
No log	2.5	50	1.4163	0.0528	1.4163	1.1901
No log	2.6	52	1.2645	0.1504	1.2645	1.1245
No log	2.7	54	1.1360	0.2059	1.1360	1.0658
No log	2.8	56	1.1180	0.2012	1.1180	1.0573
No log	2.9	58	1.1605	0.2575	1.1605	1.0773
No log	3.0	60	1.3387	0.2647	1.3387	1.1570
No log	3.1	62	1.4472	0.2879	1.4472	1.2030
No log	3.2	64	1.4385	0.2696	1.4385	1.1994
No log	3.3	66	1.2908	0.3103	1.2908	1.1361
No log	3.4	68	1.2919	0.3181	1.2919	1.1366
No log	3.5	70	1.5047	0.2777	1.5047	1.2267
No log	3.6	72	1.7909	0.1998	1.7909	1.3383
No log	3.7	74	1.8420	0.1620	1.8420	1.3572
No log	3.8	76	1.6814	0.2313	1.6814	1.2967
No log	3.9	78	1.3980	0.3329	1.3980	1.1824
No log	4.0	80	1.3197	0.3352	1.3197	1.1488
No log	4.1	82	1.3917	0.3278	1.3917	1.1797
No log	4.2	84	1.5885	0.2327	1.5885	1.2604
No log	4.3	86	1.8194	0.1949	1.8194	1.3489
No log	4.4	88	1.9486	0.1753	1.9486	1.3959
No log	4.5	90	1.9465	0.1946	1.9465	1.3952
No log	4.6	92	1.9252	0.2003	1.9252	1.3875
No log	4.7	94	1.8656	0.1956	1.8656	1.3659
No log	4.8	96	1.7333	0.2324	1.7333	1.3165
No log	4.9	98	1.6818	0.2372	1.6818	1.2968
No log	5.0	100	1.7774	0.2399	1.7774	1.3332
No log	5.1	102	1.8514	0.2104	1.8514	1.3607
No log	5.2	104	1.7371	0.2432	1.7371	1.3180
No log	5.3	106	1.5429	0.3173	1.5429	1.2421
No log	5.4	108	1.4545	0.3499	1.4545	1.2060
No log	5.5	110	1.4976	0.3393	1.4976	1.2238
No log	5.6	112	1.6208	0.2493	1.6208	1.2731
No log	5.7	114	1.7359	0.2466	1.7359	1.3175
No log	5.8	116	1.6915	0.2475	1.6915	1.3006
No log	5.9	118	1.5215	0.2986	1.5215	1.2335
No log	6.0	120	1.4868	0.3834	1.4868	1.2193
No log	6.1	122	1.4575	0.4278	1.4575	1.2073
No log	6.2	124	1.5398	0.3292	1.5398	1.2409
No log	6.3	126	1.7629	0.2399	1.7629	1.3277
No log	6.4	128	1.9123	0.2615	1.9123	1.3829
No log	6.5	130	1.9192	0.2615	1.9192	1.3854
No log	6.6	132	1.8679	0.2671	1.8679	1.3667
No log	6.7	134	1.8446	0.2219	1.8446	1.3582
No log	6.8	136	1.8490	0.2219	1.8490	1.3598
No log	6.9	138	1.8683	0.2133	1.8683	1.3669
No log	7.0	140	1.9287	0.2050	1.9287	1.3888
No log	7.1	142	2.0151	0.2029	2.0151	1.4195
No log	7.2	144	2.0284	0.2098	2.0284	1.4242
No log	7.3	146	1.9800	0.2029	1.9800	1.4071
No log	7.4	148	1.9026	0.2104	1.9026	1.3793
No log	7.5	150	1.8204	0.2116	1.8204	1.3492
No log	7.6	152	1.8184	0.2057	1.8184	1.3485
No log	7.7	154	1.7838	0.2144	1.7838	1.3356
No log	7.8	156	1.6970	0.2109	1.6970	1.3027
No log	7.9	158	1.6287	0.2469	1.6287	1.2762
No log	8.0	160	1.6100	0.2753	1.6100	1.2688
No log	8.1	162	1.6166	0.2512	1.6166	1.2715
No log	8.2	164	1.5703	0.2816	1.5703	1.2531
No log	8.3	166	1.5439	0.2986	1.5439	1.2425
No log	8.4	168	1.4723	0.3409	1.4723	1.2134
No log	8.5	170	1.4350	0.3751	1.4350	1.1979
No log	8.6	172	1.4574	0.3751	1.4574	1.2072
No log	8.7	174	1.5076	0.3275	1.5076	1.2279
No log	8.8	176	1.5772	0.2434	1.5772	1.2559
No log	8.9	178	1.6597	0.2459	1.6597	1.2883
No log	9.0	180	1.7200	0.2308	1.7200	1.3115
No log	9.1	182	1.7573	0.2483	1.7573	1.3256
No log	9.2	184	1.7641	0.2483	1.7641	1.3282
No log	9.3	186	1.7459	0.2264	1.7459	1.3213
No log	9.4	188	1.7051	0.2459	1.7051	1.3058
No log	9.5	190	1.6705	0.2459	1.6705	1.2925
No log	9.6	192	1.6530	0.2520	1.6530	1.2857
No log	9.7	194	1.6496	0.2520	1.6496	1.2844
No log	9.8	196	1.6507	0.2520	1.6507	1.2848
No log	9.9	198	1.6544	0.2520	1.6544	1.2862
No log	10.0	200	1.6558	0.2520	1.6558	1.2868

Framework versions

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