ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k12_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: 0.8829
• Qwk: 0.7052
• Mse: 0.8829
• Rmse: 0.9396

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	0.0488	2	2.1776	-0.0043	2.1776	1.4757
No log	0.0976	4	1.4670	0.2737	1.4670	1.2112
No log	0.1463	6	1.4575	0.1209	1.4575	1.2073
No log	0.1951	8	1.6327	0.1393	1.6327	1.2778
No log	0.2439	10	1.8171	0.2962	1.8171	1.3480
No log	0.2927	12	1.9824	0.2951	1.9824	1.4080
No log	0.3415	14	1.7005	0.2964	1.7005	1.3040
No log	0.3902	16	1.9050	0.2636	1.9050	1.3802
No log	0.4390	18	2.4392	0.2712	2.4392	1.5618
No log	0.4878	20	2.4439	0.2674	2.4439	1.5633
No log	0.5366	22	1.7209	0.2140	1.7209	1.3118
No log	0.5854	24	1.4103	0.1333	1.4103	1.1876
No log	0.6341	26	1.3734	0.2000	1.3734	1.1719
No log	0.6829	28	1.3942	0.2193	1.3942	1.1807
No log	0.7317	30	1.6579	0.3230	1.6579	1.2876
No log	0.7805	32	2.7363	0.0789	2.7363	1.6542
No log	0.8293	34	3.0448	-0.1437	3.0448	1.7449
No log	0.8780	36	2.7359	-0.0022	2.7359	1.6541
No log	0.9268	38	2.1690	0.2631	2.1690	1.4727
No log	0.9756	40	1.8244	0.3389	1.8244	1.3507
No log	1.0244	42	1.7216	0.3946	1.7216	1.3121
No log	1.0732	44	1.7279	0.3944	1.7279	1.3145
No log	1.1220	46	1.7898	0.3769	1.7898	1.3378
No log	1.1707	48	1.9564	0.2792	1.9564	1.3987
No log	1.2195	50	2.1324	0.2344	2.1324	1.4603
No log	1.2683	52	2.0477	0.2650	2.0477	1.4310
No log	1.3171	54	1.9256	0.3109	1.9256	1.3877
No log	1.3659	56	2.1447	0.2758	2.1447	1.4645
No log	1.4146	58	2.7943	0.3061	2.7943	1.6716
No log	1.4634	60	3.2180	0.2461	3.2180	1.7939
No log	1.5122	62	3.3065	0.2364	3.3065	1.8184
No log	1.5610	64	2.9751	0.2857	2.9751	1.7248
No log	1.6098	66	2.4484	0.3329	2.4484	1.5647
No log	1.6585	68	2.4249	0.3179	2.4249	1.5572
No log	1.7073	70	2.5961	0.3249	2.5961	1.6112
No log	1.7561	72	2.4551	0.3370	2.4551	1.5669
No log	1.8049	74	2.3486	0.3399	2.3486	1.5325
No log	1.8537	76	2.3210	0.3455	2.3210	1.5235
No log	1.9024	78	2.0418	0.4147	2.0418	1.4289
No log	1.9512	80	1.5832	0.4375	1.5832	1.2582
No log	2.0	82	1.1885	0.4583	1.1885	1.0902
No log	2.0488	84	1.0725	0.4897	1.0725	1.0356
No log	2.0976	86	1.1837	0.5037	1.1837	1.0880
No log	2.1463	88	1.4160	0.4513	1.4160	1.1900
No log	2.1951	90	1.7508	0.4313	1.7508	1.3232
No log	2.2439	92	1.6539	0.4274	1.6539	1.2860
No log	2.2927	94	1.2667	0.4836	1.2667	1.1255
No log	2.3415	96	1.0311	0.5395	1.0311	1.0154
No log	2.3902	98	1.0250	0.5385	1.0250	1.0124
No log	2.4390	100	1.2240	0.5036	1.2240	1.1063
No log	2.4878	102	1.6395	0.4633	1.6395	1.2804
No log	2.5366	104	1.7443	0.4490	1.7443	1.3207
No log	2.5854	106	1.5083	0.4677	1.5083	1.2281
No log	2.6341	108	1.2057	0.5044	1.2057	1.0981
No log	2.6829	110	1.0471	0.5539	1.0471	1.0233
No log	2.7317	112	1.0748	0.5572	1.0748	1.0367
No log	2.7805	114	1.1732	0.5512	1.1732	1.0831
No log	2.8293	116	1.2389	0.5351	1.2389	1.1131
No log	2.8780	118	1.3393	0.5224	1.3393	1.1573
No log	2.9268	120	1.4531	0.4700	1.4531	1.2055
No log	2.9756	122	1.4100	0.4570	1.4100	1.1874
No log	3.0244	124	1.3523	0.4841	1.3523	1.1629
No log	3.0732	126	1.1162	0.5433	1.1162	1.0565
No log	3.1220	128	0.9025	0.6211	0.9025	0.9500
No log	3.1707	130	0.8411	0.6528	0.8411	0.9171
No log	3.2195	132	0.8958	0.6346	0.8958	0.9465
No log	3.2683	134	1.0841	0.5564	1.0841	1.0412
No log	3.3171	136	1.5239	0.5179	1.5239	1.2345
No log	3.3659	138	1.7936	0.4764	1.7936	1.3392
No log	3.4146	140	1.6736	0.5081	1.6736	1.2937
No log	3.4634	142	1.4338	0.5212	1.4338	1.1974
No log	3.5122	144	1.1913	0.5614	1.1913	1.0915
No log	3.5610	146	0.9935	0.5807	0.9935	0.9967
No log	3.6098	148	0.9890	0.5759	0.9890	0.9945
No log	3.6585	150	1.1192	0.5737	1.1192	1.0579
No log	3.7073	152	1.3028	0.5272	1.3028	1.1414
No log	3.7561	154	1.3497	0.5068	1.3497	1.1618
No log	3.8049	156	1.3081	0.5268	1.3081	1.1437
No log	3.8537	158	1.2700	0.5528	1.2700	1.1269
No log	3.9024	160	1.2175	0.5460	1.2175	1.1034
No log	3.9512	162	1.2624	0.5528	1.2624	1.1235
No log	4.0	164	1.2040	0.5460	1.2040	1.0973
No log	4.0488	166	1.1624	0.5146	1.1624	1.0782
No log	4.0976	168	1.2153	0.5390	1.2153	1.1024
No log	4.1463	170	1.2884	0.5207	1.2884	1.1351
No log	4.1951	172	1.2406	0.5266	1.2406	1.1138
No log	4.2439	174	1.2344	0.5180	1.2344	1.1110
No log	4.2927	176	1.1339	0.5634	1.1339	1.0649
No log	4.3415	178	1.0001	0.5724	1.0001	1.0000
No log	4.3902	180	0.9820	0.5724	0.9820	0.9910
No log	4.4390	182	0.9962	0.5736	0.9962	0.9981
No log	4.4878	184	1.0317	0.5724	1.0317	1.0157
No log	4.5366	186	0.9642	0.5912	0.9642	0.9819
No log	4.5854	188	0.9582	0.5925	0.9582	0.9789
No log	4.6341	190	1.0647	0.5817	1.0647	1.0318
No log	4.6829	192	1.1724	0.5953	1.1724	1.0828
No log	4.7317	194	1.2854	0.5480	1.2854	1.1337
No log	4.7805	196	1.1949	0.5654	1.1949	1.0931
No log	4.8293	198	1.0772	0.5815	1.0772	1.0379
No log	4.8780	200	0.9390	0.6230	0.9390	0.9690
No log	4.9268	202	0.8990	0.6937	0.8990	0.9482
No log	4.9756	204	0.8536	0.7200	0.8536	0.9239
No log	5.0244	206	0.8873	0.7096	0.8873	0.9420
No log	5.0732	208	0.9426	0.6824	0.9426	0.9709
No log	5.1220	210	0.9521	0.6972	0.9521	0.9757
No log	5.1707	212	0.9908	0.6621	0.9908	0.9954
No log	5.2195	214	1.0448	0.6191	1.0448	1.0222
No log	5.2683	216	1.0262	0.6399	1.0262	1.0130
No log	5.3171	218	1.0313	0.6357	1.0313	1.0155
No log	5.3659	220	1.0070	0.6346	1.0070	1.0035
No log	5.4146	222	1.0164	0.6444	1.0164	1.0082
No log	5.4634	224	1.0020	0.6307	1.0020	1.0010
No log	5.5122	226	0.9841	0.6431	0.9841	0.9920
No log	5.5610	228	0.9581	0.6500	0.9581	0.9788
No log	5.6098	230	0.8697	0.7065	0.8697	0.9326
No log	5.6585	232	0.7707	0.7169	0.7707	0.8779
No log	5.7073	234	0.7402	0.7303	0.7402	0.8603
No log	5.7561	236	0.7672	0.7318	0.7672	0.8759
No log	5.8049	238	0.8596	0.7035	0.8596	0.9272
No log	5.8537	240	0.9153	0.6897	0.9153	0.9567
No log	5.9024	242	0.8779	0.7007	0.8779	0.9369
No log	5.9512	244	0.8222	0.7169	0.8222	0.9068
No log	6.0	246	0.8124	0.7132	0.8124	0.9014
No log	6.0488	248	0.8031	0.7132	0.8031	0.8962
No log	6.0976	250	0.8328	0.7139	0.8328	0.9126
No log	6.1463	252	0.8919	0.7096	0.8919	0.9444
No log	6.1951	254	0.9139	0.6849	0.9139	0.9560
No log	6.2439	256	0.9437	0.6600	0.9437	0.9714
No log	6.2927	258	0.8956	0.6734	0.8956	0.9464
No log	6.3415	260	0.7949	0.7139	0.7949	0.8916
No log	6.3902	262	0.7525	0.7228	0.7525	0.8675
No log	6.4390	264	0.7286	0.7227	0.7286	0.8536
No log	6.4878	266	0.7543	0.7228	0.7543	0.8685
No log	6.5366	268	0.8284	0.7065	0.8284	0.9102
No log	6.5854	270	0.8707	0.7150	0.8707	0.9331
No log	6.6341	272	0.9398	0.6896	0.9398	0.9694
No log	6.6829	274	0.9539	0.6896	0.9539	0.9767
No log	6.7317	276	0.8816	0.7339	0.8816	0.9389
No log	6.7805	278	0.8394	0.7339	0.8394	0.9162
No log	6.8293	280	0.8254	0.7362	0.8254	0.9085
No log	6.8780	282	0.8863	0.7339	0.8863	0.9414
No log	6.9268	284	0.9617	0.6785	0.9617	0.9807
No log	6.9756	286	0.9721	0.6569	0.9721	0.9859
No log	7.0244	288	0.9344	0.6558	0.9344	0.9666
No log	7.0732	290	0.8612	0.7155	0.8612	0.9280
No log	7.1220	292	0.7831	0.7200	0.7831	0.8849
No log	7.1707	294	0.7572	0.7125	0.7572	0.8702
No log	7.2195	296	0.7545	0.7125	0.7545	0.8686
No log	7.2683	298	0.7663	0.7125	0.7663	0.8754
No log	7.3171	300	0.8198	0.7200	0.8198	0.9054
No log	7.3659	302	0.8850	0.7079	0.8850	0.9408
No log	7.4146	304	0.9951	0.6673	0.9951	0.9975
No log	7.4634	306	1.0514	0.6163	1.0514	1.0254
No log	7.5122	308	1.0230	0.6346	1.0230	1.0114
No log	7.5610	310	0.9410	0.6750	0.9410	0.9700
No log	7.6098	312	0.8384	0.7200	0.8384	0.9157
No log	7.6585	314	0.7859	0.7162	0.7859	0.8865
No log	7.7073	316	0.7724	0.7125	0.7724	0.8788
No log	7.7561	318	0.7985	0.7162	0.7985	0.8936
No log	7.8049	320	0.8728	0.7180	0.8728	0.9342
No log	7.8537	322	0.9145	0.7059	0.9145	0.9563
No log	7.9024	324	0.9143	0.7059	0.9143	0.9562
No log	7.9512	326	0.8637	0.7282	0.8637	0.9294
No log	8.0	328	0.8436	0.7282	0.8436	0.9185
No log	8.0488	330	0.8645	0.7180	0.8645	0.9298
No log	8.0976	332	0.8650	0.7180	0.8650	0.9301
No log	8.1463	334	0.8737	0.7180	0.8737	0.9347
No log	8.1951	336	0.8851	0.7180	0.8851	0.9408
No log	8.2439	338	0.8686	0.7180	0.8686	0.9320
No log	8.2927	340	0.8423	0.7282	0.8423	0.9178
No log	8.3415	342	0.8150	0.7200	0.8150	0.9028
No log	8.3902	344	0.8155	0.7200	0.8155	0.9031
No log	8.4390	346	0.8061	0.7200	0.8061	0.8978
No log	8.4878	348	0.8049	0.7200	0.8049	0.8972
No log	8.5366	350	0.8282	0.7200	0.8282	0.9100
No log	8.5854	352	0.8572	0.7200	0.8572	0.9258
No log	8.6341	354	0.8703	0.7200	0.8703	0.9329
No log	8.6829	356	0.8904	0.7052	0.8904	0.9436
No log	8.7317	358	0.8940	0.7096	0.8940	0.9455
No log	8.7805	360	0.8851	0.7096	0.8851	0.9408
No log	8.8293	362	0.8949	0.7180	0.8949	0.9460
No log	8.8780	364	0.9189	0.6855	0.9189	0.9586
No log	8.9268	366	0.9476	0.6758	0.9476	0.9734
No log	8.9756	368	0.9573	0.6758	0.9573	0.9784
No log	9.0244	370	0.9488	0.6758	0.9488	0.9741
No log	9.0732	372	0.9199	0.6855	0.9199	0.9591
No log	9.1220	374	0.8867	0.7052	0.8867	0.9416
No log	9.1707	376	0.8602	0.7200	0.8602	0.9275
No log	9.2195	378	0.8398	0.7200	0.8398	0.9164
No log	9.2683	380	0.8344	0.7200	0.8344	0.9135
No log	9.3171	382	0.8349	0.7200	0.8349	0.9137
No log	9.3659	384	0.8410	0.7200	0.8410	0.9171
No log	9.4146	386	0.8453	0.7200	0.8453	0.9194
No log	9.4634	388	0.8498	0.7200	0.8498	0.9219
No log	9.5122	390	0.8604	0.7200	0.8604	0.9276
No log	9.5610	392	0.8719	0.7096	0.8719	0.9337
No log	9.6098	394	0.8838	0.7052	0.8838	0.9401
No log	9.6585	396	0.8923	0.7052	0.8923	0.9446
No log	9.7073	398	0.8970	0.6950	0.8970	0.9471
No log	9.7561	400	0.8981	0.6950	0.8981	0.9477
No log	9.8049	402	0.8935	0.6950	0.8935	0.9453
No log	9.8537	404	0.8886	0.7052	0.8886	0.9426
No log	9.9024	406	0.8849	0.7052	0.8849	0.9407
No log	9.9512	408	0.8835	0.7052	0.8835	0.9399
No log	10.0	410	0.8829	0.7052	0.8829	0.9396

Framework versions

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