ArabicNewSplits8_FineTuningAraBERT_noAug_task4_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: 1.1578
• Qwk: -0.0455
• Mse: 1.1578
• Rmse: 1.0760

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.6667	2	5.9204	-0.0168	5.9204	2.4332
No log	1.3333	4	3.8580	-0.0985	3.8580	1.9642
No log	2.0	6	1.9360	-0.1000	1.9360	1.3914
No log	2.6667	8	1.2794	-0.1415	1.2794	1.1311
No log	3.3333	10	1.2565	-0.1163	1.2565	1.1209
No log	4.0	12	1.8380	-0.2093	1.8380	1.3557
No log	4.6667	14	1.8848	-0.1754	1.8848	1.3729
No log	5.3333	16	2.2755	-0.1874	2.2755	1.5085
No log	6.0	18	2.2763	-0.1832	2.2763	1.5088
No log	6.6667	20	1.7516	-0.1321	1.7516	1.3235
No log	7.3333	22	1.4979	-0.1579	1.4979	1.2239
No log	8.0	24	1.4029	-0.2072	1.4029	1.1845
No log	8.6667	26	1.3581	-0.1880	1.3581	1.1654
No log	9.3333	28	1.3189	-0.2277	1.3189	1.1484
No log	10.0	30	1.2172	-0.0652	1.2172	1.1033
No log	10.6667	32	1.1941	-0.0513	1.1941	1.0927
No log	11.3333	34	1.1486	-0.0817	1.1486	1.0717
No log	12.0	36	1.2427	-0.0690	1.2427	1.1148
No log	12.6667	38	1.3718	-0.0655	1.3718	1.1712
No log	13.3333	40	1.2895	-0.0623	1.2895	1.1355
No log	14.0	42	1.2825	-0.1097	1.2825	1.1325
No log	14.6667	44	1.3660	-0.1976	1.3660	1.1688
No log	15.3333	46	1.3971	-0.1239	1.3971	1.1820
No log	16.0	48	1.4523	-0.1498	1.4523	1.2051
No log	16.6667	50	1.4551	-0.2685	1.4551	1.2063
No log	17.3333	52	1.3642	-0.2589	1.3642	1.1680
No log	18.0	54	1.2834	-0.1345	1.2834	1.1329
No log	18.6667	56	1.3153	-0.1238	1.3153	1.1469
No log	19.3333	58	1.4973	-0.2612	1.4973	1.2237
No log	20.0	60	1.6327	-0.1554	1.6327	1.2778
No log	20.6667	62	1.4672	-0.1009	1.4672	1.2113
No log	21.3333	64	1.3410	-0.1481	1.3410	1.1580
No log	22.0	66	1.3545	-0.1394	1.3545	1.1638
No log	22.6667	68	1.5025	-0.0935	1.5025	1.2258
No log	23.3333	70	1.5746	-0.2137	1.5746	1.2548
No log	24.0	72	1.5052	-0.1807	1.5052	1.2269
No log	24.6667	74	1.3492	-0.1367	1.3492	1.1615
No log	25.3333	76	1.3460	-0.1097	1.3460	1.1602
No log	26.0	78	1.2371	-0.2733	1.2371	1.1122
No log	26.6667	80	1.2849	0.1397	1.2849	1.1335
No log	27.3333	82	1.3523	-0.0525	1.3523	1.1629
No log	28.0	84	1.2869	0.1206	1.2869	1.1344
No log	28.6667	86	1.1979	0.0271	1.1979	1.0945
No log	29.3333	88	1.2024	-0.0616	1.2024	1.0965
No log	30.0	90	1.2214	-0.0100	1.2214	1.1052
No log	30.6667	92	1.3249	-0.1805	1.3249	1.1510
No log	31.3333	94	1.3365	-0.2072	1.3365	1.1561
No log	32.0	96	1.2836	0.0418	1.2836	1.1329
No log	32.6667	98	1.2571	0.0067	1.2571	1.1212
No log	33.3333	100	1.2612	0.0558	1.2612	1.1230
No log	34.0	102	1.3075	0.0195	1.3075	1.1435
No log	34.6667	104	1.3924	-0.0924	1.3924	1.1800
No log	35.3333	106	1.5376	-0.1285	1.5376	1.2400
No log	36.0	108	1.5649	-0.0972	1.5649	1.2510
No log	36.6667	110	1.4357	-0.0259	1.4357	1.1982
No log	37.3333	112	1.2533	0.0412	1.2533	1.1195
No log	38.0	114	1.1760	0.0771	1.1760	1.0844
No log	38.6667	116	1.1396	0.0771	1.1396	1.0675
No log	39.3333	118	1.1502	0.0386	1.1502	1.0725
No log	40.0	120	1.1707	0.0386	1.1707	1.0820
No log	40.6667	122	1.1921	0.0558	1.1921	1.0918
No log	41.3333	124	1.2350	-0.0095	1.2350	1.1113
No log	42.0	126	1.2071	-0.0095	1.2071	1.0987
No log	42.6667	128	1.1615	-0.0854	1.1615	1.0777
No log	43.3333	130	1.1584	-0.0850	1.1584	1.0763
No log	44.0	132	1.1811	-0.1151	1.1811	1.0868
No log	44.6667	134	1.2010	-0.1097	1.2010	1.0959
No log	45.3333	136	1.2743	-0.0271	1.2743	1.1289
No log	46.0	138	1.2960	-0.1022	1.2960	1.1384
No log	46.6667	140	1.3170	-0.2072	1.3170	1.1476
No log	47.3333	142	1.2513	-0.0433	1.2513	1.1186
No log	48.0	144	1.1718	0.0531	1.1718	1.0825
No log	48.6667	146	1.1741	-0.1224	1.1741	1.0835
No log	49.3333	148	1.1981	-0.1540	1.1981	1.0946
No log	50.0	150	1.2483	-0.0095	1.2483	1.1173
No log	50.6667	152	1.3471	-0.0554	1.3471	1.1606
No log	51.3333	154	1.3759	-0.1464	1.3759	1.1730
No log	52.0	156	1.3140	-0.1741	1.3140	1.1463
No log	52.6667	158	1.2224	-0.0427	1.2224	1.1056
No log	53.3333	160	1.1527	0.0067	1.1527	1.0736
No log	54.0	162	1.0923	0.1127	1.0923	1.0451
No log	54.6667	164	1.0634	0.0238	1.0634	1.0312
No log	55.3333	166	1.0745	0.1591	1.0745	1.0366
No log	56.0	168	1.1132	0.1507	1.1132	1.0551
No log	56.6667	170	1.1655	0.0591	1.1655	1.0796
No log	57.3333	172	1.1974	0.0418	1.1974	1.0943
No log	58.0	174	1.1892	0.0238	1.1892	1.0905
No log	58.6667	176	1.2503	-0.0275	1.2503	1.1182
No log	59.3333	178	1.2641	-0.0275	1.2641	1.1243
No log	60.0	180	1.2830	-0.0265	1.2830	1.1327
No log	60.6667	182	1.2787	0.0101	1.2787	1.1308
No log	61.3333	184	1.2386	0.0474	1.2386	1.1129
No log	62.0	186	1.1705	0.0835	1.1705	1.0819
No log	62.6667	188	1.0928	0.1397	1.0928	1.0454
No log	63.3333	190	1.0399	0.0622	1.0399	1.0198
No log	64.0	192	1.0266	0.1533	1.0266	1.0132
No log	64.6667	194	1.0338	0.0987	1.0338	1.0167
No log	65.3333	196	1.0417	0.0987	1.0417	1.0207
No log	66.0	198	1.0641	0.0766	1.0641	1.0316
No log	66.6667	200	1.1138	0.0731	1.1138	1.0554
No log	67.3333	202	1.1669	0.0560	1.1669	1.0802
No log	68.0	204	1.1792	0.0392	1.1792	1.0859
No log	68.6667	206	1.1604	0.0392	1.1604	1.0772
No log	69.3333	208	1.1420	0.0064	1.1420	1.0687
No log	70.0	210	1.1363	0.0226	1.1363	1.0660
No log	70.6667	212	1.1500	-0.0100	1.1500	1.0724
No log	71.3333	214	1.1589	-0.0100	1.1589	1.0765
No log	72.0	216	1.1504	0.0226	1.1504	1.0726
No log	72.6667	218	1.1563	-0.0461	1.1563	1.0753
No log	73.3333	220	1.1763	0.0216	1.1763	1.0846
No log	74.0	222	1.2127	0.0731	1.2127	1.1012
No log	74.6667	224	1.2293	0.0049	1.2293	1.1087
No log	75.3333	226	1.2276	0.0049	1.2276	1.1080
No log	76.0	228	1.2164	-0.0114	1.2164	1.1029
No log	76.6667	230	1.1913	0.0560	1.1913	1.0915
No log	77.3333	232	1.1687	0.0560	1.1687	1.0810
No log	78.0	234	1.1487	0.0392	1.1487	1.0718
No log	78.6667	236	1.1456	-0.0455	1.1456	1.0703
No log	79.3333	238	1.1327	-0.0100	1.1327	1.0643
No log	80.0	240	1.1271	-0.0455	1.1271	1.0616
No log	80.6667	242	1.1153	-0.0289	1.1153	1.0561
No log	81.3333	244	1.1123	-0.0486	1.1123	1.0547
No log	82.0	246	1.1203	-0.0120	1.1203	1.0584
No log	82.6667	248	1.1301	-0.0289	1.1301	1.0631
No log	83.3333	250	1.1288	-0.0289	1.1288	1.0624
No log	84.0	252	1.1253	-0.0289	1.1253	1.0608
No log	84.6667	254	1.1214	0.0067	1.1214	1.0590
No log	85.3333	256	1.1279	0.0238	1.1279	1.0620
No log	86.0	258	1.1485	0.0392	1.1485	1.0717
No log	86.6667	260	1.1709	-0.0275	1.1709	1.0821
No log	87.3333	262	1.1837	0.0067	1.1837	1.0880
No log	88.0	264	1.1968	-0.0100	1.1968	1.0940
No log	88.6667	266	1.2095	-0.0100	1.2095	1.0998
No log	89.3333	268	1.2158	-0.0100	1.2158	1.1026
No log	90.0	270	1.2235	-0.0100	1.2235	1.1061
No log	90.6667	272	1.2301	-0.0100	1.2301	1.1091
No log	91.3333	274	1.2391	-0.0100	1.2391	1.1132
No log	92.0	276	1.2413	-0.0265	1.2413	1.1142
No log	92.6667	278	1.2386	-0.0265	1.2386	1.1129
No log	93.3333	280	1.2290	0.0082	1.2290	1.1086
No log	94.0	282	1.2154	-0.0252	1.2154	1.1025
No log	94.6667	284	1.2004	-0.0433	1.2004	1.0956
No log	95.3333	286	1.1914	-0.0433	1.1914	1.0915
No log	96.0	288	1.1847	-0.0433	1.1847	1.0884
No log	96.6667	290	1.1772	-0.0618	1.1772	1.0850
No log	97.3333	292	1.1694	-0.0618	1.1694	1.0814
No log	98.0	294	1.1647	-0.0618	1.1647	1.0792
No log	98.6667	296	1.1606	-0.0618	1.1606	1.0773
No log	99.3333	298	1.1585	-0.0455	1.1585	1.0763
No log	100.0	300	1.1578	-0.0455	1.1578	1.0760

Framework versions

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