Arabic_FineTuningAraBERT_run3_AugV5_k3_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: 0.5976
• Qwk: 0.6807
• Mse: 0.5976
• Rmse: 0.7731

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	4.2434	0.0	4.2434	2.0599
No log	0.0976	4	2.0834	-0.0199	2.0834	1.4434
No log	0.1463	6	1.2590	0.0278	1.2590	1.1221
No log	0.1951	8	1.1294	-0.0225	1.1294	1.0628
No log	0.2439	10	1.0988	-0.0856	1.0988	1.0482
No log	0.2927	12	1.1084	0.0421	1.1084	1.0528
No log	0.3415	14	1.4085	0.0	1.4085	1.1868
No log	0.3902	16	1.6147	0.0	1.6147	1.2707
No log	0.4390	18	1.6122	0.0	1.6122	1.2697
No log	0.4878	20	1.6622	0.0	1.6622	1.2893
No log	0.5366	22	1.6090	0.0	1.6090	1.2685
No log	0.5854	24	1.5963	0.0	1.5963	1.2634
No log	0.6341	26	1.5530	0.0	1.5530	1.2462
No log	0.6829	28	1.4893	0.0	1.4893	1.2204
No log	0.7317	30	1.3154	0.0841	1.3154	1.1469
No log	0.7805	32	1.1259	0.1706	1.1259	1.0611
No log	0.8293	34	1.0943	0.0297	1.0943	1.0461
No log	0.8780	36	1.1667	0.0780	1.1667	1.0801
No log	0.9268	38	1.3950	0.2162	1.3950	1.1811
No log	0.9756	40	1.5272	0.1720	1.5272	1.2358
No log	1.0244	42	1.5172	0.1720	1.5172	1.2318
No log	1.0732	44	1.4565	0.0755	1.4565	1.2068
No log	1.1220	46	1.1530	0.0780	1.1530	1.0738
No log	1.1707	48	0.9236	0.1878	0.9236	0.9610
No log	1.2195	50	0.8774	0.1566	0.8774	0.9367
No log	1.2683	52	0.8767	0.1840	0.8767	0.9363
No log	1.3171	54	0.8839	0.0562	0.8839	0.9401
No log	1.3659	56	0.9107	0.1895	0.9107	0.9543
No log	1.4146	58	0.8868	0.1390	0.8868	0.9417
No log	1.4634	60	0.8588	0.1600	0.8588	0.9267
No log	1.5122	62	0.8496	0.1302	0.8496	0.9217
No log	1.5610	64	0.8401	0.1860	0.8401	0.9166
No log	1.6098	66	0.8237	0.24	0.8237	0.9076
No log	1.6585	68	0.8789	0.0982	0.8789	0.9375
No log	1.7073	70	1.0717	0.0473	1.0717	1.0352
No log	1.7561	72	1.3396	-0.1011	1.3396	1.1574
No log	1.8049	74	1.4482	-0.0652	1.4482	1.2034
No log	1.8537	76	1.2731	-0.0442	1.2731	1.1283
No log	1.9024	78	0.9781	0.0233	0.9781	0.9890
No log	1.9512	80	0.8499	0.1878	0.8499	0.9219
No log	2.0	82	0.8369	0.3913	0.8369	0.9148
No log	2.0488	84	0.8601	0.4776	0.8601	0.9274
No log	2.0976	86	0.8627	0.4776	0.8627	0.9288
No log	2.1463	88	0.8118	0.4776	0.8118	0.9010
No log	2.1951	90	0.7299	0.3425	0.7299	0.8543
No log	2.2439	92	0.7534	0.2959	0.7534	0.8680
No log	2.2927	94	0.8065	0.2811	0.8065	0.8981
No log	2.3415	96	0.7870	0.3770	0.7870	0.8871
No log	2.3902	98	0.7655	0.5205	0.7655	0.8749
No log	2.4390	100	0.7180	0.5950	0.7180	0.8474
No log	2.4878	102	0.7411	0.5950	0.7411	0.8609
No log	2.5366	104	0.7715	0.5950	0.7715	0.8784
No log	2.5854	106	0.8404	0.6182	0.8404	0.9167
No log	2.6341	108	0.9670	0.3510	0.9670	0.9833
No log	2.6829	110	1.1121	0.3546	1.1121	1.0546
No log	2.7317	112	1.3283	0.0345	1.3283	1.1525
No log	2.7805	114	1.3408	0.0345	1.3408	1.1579
No log	2.8293	116	1.1114	0.2602	1.1114	1.0542
No log	2.8780	118	0.9188	0.4368	0.9188	0.9585
No log	2.9268	120	0.8385	0.5267	0.8385	0.9157
No log	2.9756	122	0.8304	0.5128	0.8304	0.9112
No log	3.0244	124	0.8266	0.5405	0.8266	0.9092
No log	3.0732	126	0.8154	0.5372	0.8154	0.9030
No log	3.1220	128	0.8738	0.3519	0.8738	0.9348
No log	3.1707	130	1.1288	0.1667	1.1288	1.0625
No log	3.2195	132	1.2579	-0.0460	1.2579	1.1216
No log	3.2683	134	1.1818	-0.0736	1.1818	1.0871
No log	3.3171	136	0.9631	0.125	0.9631	0.9814
No log	3.3659	138	0.7555	0.3959	0.7555	0.8692
No log	3.4146	140	0.7123	0.4306	0.7123	0.8440
No log	3.4634	142	0.7302	0.4388	0.7302	0.8545
No log	3.5122	144	0.7444	0.4815	0.7444	0.8628
No log	3.5610	146	0.7526	0.6182	0.7526	0.8675
No log	3.6098	148	0.7267	0.6182	0.7267	0.8525
No log	3.6585	150	0.7192	0.6182	0.7192	0.8481
No log	3.7073	152	0.7371	0.6316	0.7371	0.8585
No log	3.7561	154	0.7813	0.6316	0.7813	0.8839
No log	3.8049	156	0.9194	0.4690	0.9194	0.9589
No log	3.8537	158	0.9759	0.4878	0.9759	0.9879
No log	3.9024	160	0.8938	0.4878	0.8938	0.9454
No log	3.9512	162	0.7444	0.6209	0.7444	0.8628
No log	4.0	164	0.6854	0.6316	0.6854	0.8279
No log	4.0488	166	0.6560	0.6316	0.6560	0.8100
No log	4.0976	168	0.5668	0.6094	0.5668	0.7528
No log	4.1463	170	0.5275	0.5847	0.5275	0.7263
No log	4.1951	172	0.5301	0.5984	0.5301	0.7281
No log	4.2439	174	0.5512	0.6316	0.5512	0.7424
No log	4.2927	176	0.5702	0.6316	0.5702	0.7551
No log	4.3415	178	0.6269	0.6316	0.6269	0.7918
No log	4.3902	180	0.7119	0.6525	0.7119	0.8438
No log	4.4390	182	0.7504	0.6237	0.7504	0.8662
No log	4.4878	184	0.7558	0.6138	0.7558	0.8694
No log	4.5366	186	0.6337	0.6738	0.6337	0.7960
No log	4.5854	188	0.4731	0.6715	0.4731	0.6878
No log	4.6341	190	0.4055	0.6513	0.4055	0.6368
No log	4.6829	192	0.3919	0.6513	0.3919	0.6260
No log	4.7317	194	0.3825	0.6513	0.3825	0.6184
No log	4.7805	196	0.3759	0.664	0.3759	0.6131
No log	4.8293	198	0.3704	0.6513	0.3704	0.6086
No log	4.8780	200	0.4024	0.7	0.4024	0.6344
No log	4.9268	202	0.5032	0.6715	0.5032	0.7094
No log	4.9756	204	0.5496	0.6423	0.5496	0.7413
No log	5.0244	206	0.5028	0.6715	0.5028	0.7091
No log	5.0732	208	0.4923	0.7143	0.4923	0.7016
No log	5.1220	210	0.5159	0.7143	0.5159	0.7183
No log	5.1707	212	0.5303	0.7143	0.5303	0.7282
No log	5.2195	214	0.5753	0.6715	0.5753	0.7585
No log	5.2683	216	0.6273	0.6597	0.6273	0.7920
No log	5.3171	218	0.6406	0.6597	0.6406	0.8004
No log	5.3659	220	0.5495	0.6715	0.5495	0.7413
No log	5.4146	222	0.4648	0.7407	0.4648	0.6818
No log	5.4634	224	0.4261	0.6397	0.4261	0.6528
No log	5.5122	226	0.4378	0.6715	0.4378	0.6617
No log	5.5610	228	0.4294	0.6715	0.4294	0.6553
No log	5.6098	230	0.4464	0.6715	0.4464	0.6681
No log	5.6585	232	0.4305	0.6715	0.4305	0.6561
No log	5.7073	234	0.4039	0.6715	0.4039	0.6355
No log	5.7561	236	0.4271	0.6715	0.4271	0.6536
No log	5.8049	238	0.4809	0.6715	0.4809	0.6934
No log	5.8537	240	0.5207	0.6715	0.5207	0.7216
No log	5.9024	242	0.5343	0.6715	0.5343	0.7309
No log	5.9512	244	0.4977	0.6715	0.4977	0.7055
No log	6.0	246	0.5174	0.6715	0.5174	0.7193
No log	6.0488	248	0.4909	0.6715	0.4909	0.7006
No log	6.0976	250	0.4998	0.7143	0.4998	0.7069
No log	6.1463	252	0.5231	0.6715	0.5231	0.7233
No log	6.1951	254	0.5966	0.6807	0.5966	0.7724
No log	6.2439	256	0.6146	0.6807	0.6146	0.7840
No log	6.2927	258	0.6168	0.6597	0.6168	0.7854
No log	6.3415	260	0.6227	0.6597	0.6227	0.7891
No log	6.3902	262	0.6167	0.6597	0.6167	0.7853
No log	6.4390	264	0.5896	0.7016	0.5896	0.7678
No log	6.4878	266	0.5405	0.7143	0.5405	0.7352
No log	6.5366	268	0.5243	0.7143	0.5243	0.7241
No log	6.5854	270	0.4937	0.7143	0.4937	0.7026
No log	6.6341	272	0.4705	0.6715	0.4705	0.6859
No log	6.6829	274	0.4599	0.6715	0.4599	0.6781
No log	6.7317	276	0.4870	0.6715	0.4870	0.6979
No log	6.7805	278	0.4943	0.6715	0.4943	0.7031
No log	6.8293	280	0.4664	0.6715	0.4664	0.6829
No log	6.8780	282	0.5032	0.6715	0.5032	0.7094
No log	6.9268	284	0.5100	0.6715	0.5100	0.7141
No log	6.9756	286	0.5262	0.6715	0.5262	0.7254
No log	7.0244	288	0.5184	0.6715	0.5184	0.7200
No log	7.0732	290	0.5763	0.6807	0.5763	0.7592
No log	7.1220	292	0.6432	0.6807	0.6432	0.8020
No log	7.1707	294	0.7266	0.6416	0.7266	0.8524
No log	7.2195	296	0.7415	0.6416	0.7415	0.8611
No log	7.2683	298	0.6886	0.6807	0.6886	0.8298
No log	7.3171	300	0.6283	0.6597	0.6283	0.7927
No log	7.3659	302	0.6253	0.6807	0.6253	0.7908
No log	7.4146	304	0.6225	0.6807	0.6225	0.7890
No log	7.4634	306	0.6255	0.6807	0.6255	0.7909
No log	7.5122	308	0.5904	0.6807	0.5904	0.7684
No log	7.5610	310	0.5745	0.6807	0.5745	0.7580
No log	7.6098	312	0.5193	0.6715	0.5193	0.7206
No log	7.6585	314	0.4758	0.6715	0.4758	0.6898
No log	7.7073	316	0.4148	0.75	0.4148	0.6440
No log	7.7561	318	0.3682	0.7603	0.3682	0.6068
No log	7.8049	320	0.3579	0.7603	0.3579	0.5983
No log	7.8537	322	0.3650	0.7921	0.3650	0.6041
No log	7.9024	324	0.4031	0.75	0.4031	0.6349
No log	7.9512	326	0.4946	0.6715	0.4946	0.7033
No log	8.0	328	0.5870	0.6934	0.5870	0.7661
No log	8.0488	330	0.6028	0.7021	0.6028	0.7764
No log	8.0976	332	0.5659	0.6934	0.5659	0.7523
No log	8.1463	334	0.5083	0.6715	0.5083	0.7130
No log	8.1951	336	0.4514	0.6715	0.4514	0.6718
No log	8.2439	338	0.4449	0.7143	0.4449	0.6670
No log	8.2927	340	0.4773	0.6715	0.4773	0.6909
No log	8.3415	342	0.5515	0.6934	0.5515	0.7426
No log	8.3902	344	0.6515	0.6807	0.6515	0.8071
No log	8.4390	346	0.7424	0.6478	0.7424	0.8616
No log	8.4878	348	0.7754	0.5706	0.7754	0.8806
No log	8.5366	350	0.7604	0.6222	0.7604	0.8720
No log	8.5854	352	0.7051	0.7021	0.7051	0.8397
No log	8.6341	354	0.6343	0.6807	0.6343	0.7964
No log	8.6829	356	0.5583	0.6807	0.5583	0.7472
No log	8.7317	358	0.4987	0.6715	0.4987	0.7062
No log	8.7805	360	0.4665	0.6715	0.4665	0.6830
No log	8.8293	362	0.4368	0.7143	0.4368	0.6609
No log	8.8780	364	0.4296	0.7143	0.4296	0.6555
No log	8.9268	366	0.4466	0.6715	0.4466	0.6683
No log	8.9756	368	0.4849	0.6715	0.4849	0.6964
No log	9.0244	370	0.5295	0.6934	0.5295	0.7277
No log	9.0732	372	0.5641	0.6807	0.5641	0.7511
No log	9.1220	374	0.5932	0.6807	0.5932	0.7702
No log	9.1707	376	0.6009	0.6807	0.6009	0.7752
No log	9.2195	378	0.5989	0.6807	0.5989	0.7739
No log	9.2683	380	0.6140	0.7021	0.6140	0.7836
No log	9.3171	382	0.6166	0.7021	0.6166	0.7852
No log	9.3659	384	0.6215	0.7021	0.6215	0.7883
No log	9.4146	386	0.6253	0.7021	0.6253	0.7908
No log	9.4634	388	0.6257	0.6807	0.6257	0.7910
No log	9.5122	390	0.6227	0.6807	0.6227	0.7891
No log	9.5610	392	0.6205	0.6807	0.6205	0.7877
No log	9.6098	394	0.6307	0.7021	0.6307	0.7942
No log	9.6585	396	0.6363	0.7021	0.6363	0.7977
No log	9.7073	398	0.6331	0.7021	0.6331	0.7957
No log	9.7561	400	0.6233	0.6807	0.6233	0.7895
No log	9.8049	402	0.6150	0.6807	0.6150	0.7842
No log	9.8537	404	0.6073	0.6807	0.6073	0.7793
No log	9.9024	406	0.6025	0.6807	0.6025	0.7762
No log	9.9512	408	0.5996	0.6807	0.5996	0.7743
No log	10.0	410	0.5976	0.6807	0.5976	0.7731

Framework versions

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