Arabic_FineTuningAraBERT_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: 0.5210
• Qwk: 0.6667
• Mse: 0.5210
• Rmse: 0.7218

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	4.7697	-0.0600	4.7697	2.1840
No log	0.0976	4	3.1355	-0.1473	3.1355	1.7707
No log	0.1463	6	2.0981	-0.0448	2.0981	1.4485
No log	0.1951	8	1.4042	0.1212	1.4042	1.1850
No log	0.2439	10	1.2604	0.0571	1.2604	1.1227
No log	0.2927	12	1.0698	0.2648	1.0698	1.0343
No log	0.3415	14	0.9898	0.0233	0.9898	0.9949
No log	0.3902	16	1.1031	-0.1011	1.1031	1.0503
No log	0.4390	18	1.2000	-0.0652	1.2000	1.0955
No log	0.4878	20	1.4698	-0.0467	1.4698	1.2124
No log	0.5366	22	1.7756	-0.0769	1.7756	1.3325
No log	0.5854	24	1.8902	-0.0769	1.8902	1.3748
No log	0.6341	26	1.8247	-0.0769	1.8247	1.3508
No log	0.6829	28	1.6428	0.0	1.6428	1.2817
No log	0.7317	30	1.4880	0.0	1.4880	1.2199
No log	0.7805	32	1.4574	0.0	1.4574	1.2072
No log	0.8293	34	1.3712	0.0	1.3712	1.1710
No log	0.8780	36	1.1198	0.0	1.1198	1.0582
No log	0.9268	38	0.9357	0.2143	0.9357	0.9673
No log	0.9756	40	0.9383	0.2613	0.9383	0.9687
No log	1.0244	42	1.0042	0.0841	1.0042	1.0021
No log	1.0732	44	1.1832	0.0	1.1832	1.0878
No log	1.1220	46	1.4620	0.0	1.4620	1.2092
No log	1.1707	48	1.5122	0.0	1.5122	1.2297
No log	1.2195	50	1.3170	0.0	1.3170	1.1476
No log	1.2683	52	1.2467	0.0	1.2467	1.1166
No log	1.3171	54	1.1174	0.0841	1.1174	1.0571
No log	1.3659	56	0.9839	0.1250	0.9839	0.9919
No log	1.4146	58	0.8567	0.5746	0.8567	0.9256
No log	1.4634	60	0.7866	0.3488	0.7866	0.8869
No log	1.5122	62	0.7791	0.2130	0.7791	0.8826
No log	1.5610	64	0.7637	0.2130	0.7637	0.8739
No log	1.6098	66	0.7389	0.2130	0.7389	0.8596
No log	1.6585	68	0.7178	0.2130	0.7178	0.8472
No log	1.7073	70	0.7076	0.2130	0.7076	0.8412
No log	1.7561	72	0.7177	0.5134	0.7177	0.8472
No log	1.8049	74	0.8028	0.5285	0.8028	0.8960
No log	1.8537	76	0.9262	0.3069	0.9262	0.9624
No log	1.9024	78	1.0297	0.1923	1.0297	1.0147
No log	1.9512	80	0.9455	0.4286	0.9455	0.9724
No log	2.0	82	0.8420	0.4286	0.8420	0.9176
No log	2.0488	84	0.7686	0.5285	0.7686	0.8767
No log	2.0976	86	0.7756	0.5285	0.7756	0.8807
No log	2.1463	88	0.7172	0.4842	0.7172	0.8469
No log	2.1951	90	0.6419	0.4	0.6419	0.8012
No log	2.2439	92	0.6369	0.4	0.6369	0.7981
No log	2.2927	94	0.6549	0.4	0.6549	0.8093
No log	2.3415	96	0.6790	0.4	0.6790	0.8240
No log	2.3902	98	0.6775	0.4	0.6775	0.8231
No log	2.4390	100	0.6362	0.4	0.6362	0.7976
No log	2.4878	102	0.6250	0.3787	0.6250	0.7906
No log	2.5366	104	0.7213	0.4192	0.7213	0.8493
No log	2.5854	106	0.6907	0.4192	0.6907	0.8311
No log	2.6341	108	0.5621	0.5374	0.5621	0.7497
No log	2.6829	110	0.5105	0.6500	0.5105	0.7145
No log	2.7317	112	0.5263	0.6557	0.5263	0.7255
No log	2.7805	114	0.6361	0.5447	0.6361	0.7975
No log	2.8293	116	0.8101	0.5447	0.8101	0.9000
No log	2.8780	118	0.7786	0.4878	0.7786	0.8824
No log	2.9268	120	0.6508	0.5783	0.6508	0.8067
No log	2.9756	122	0.5822	0.6008	0.5822	0.7630
No log	3.0244	124	0.5574	0.7287	0.5574	0.7466
No log	3.0732	126	0.5347	0.7364	0.5347	0.7312
No log	3.1220	128	0.5502	0.6182	0.5502	0.7418
No log	3.1707	130	0.5576	0.6930	0.5576	0.7467
No log	3.2195	132	0.5905	0.6111	0.5905	0.7684
No log	3.2683	134	0.6140	0.6111	0.6140	0.7836
No log	3.3171	136	0.6054	0.6111	0.6054	0.7781
No log	3.3659	138	0.5698	0.6111	0.5698	0.7549
No log	3.4146	140	0.5550	0.6111	0.5550	0.7450
No log	3.4634	142	0.5186	0.7822	0.5186	0.7201
No log	3.5122	144	0.5076	0.6897	0.5076	0.7124
No log	3.5610	146	0.5012	0.5845	0.5012	0.7080
No log	3.6098	148	0.5031	0.6224	0.5031	0.7093
No log	3.6585	150	0.4957	0.7131	0.4957	0.7041
No log	3.7073	152	0.5277	0.6345	0.5277	0.7265
No log	3.7561	154	0.5684	0.5914	0.5684	0.7539
No log	3.8049	156	0.7120	0.4878	0.7120	0.8438
No log	3.8537	158	0.7473	0.4878	0.7473	0.8645
No log	3.9024	160	0.7977	0.4878	0.7977	0.8932
No log	3.9512	162	0.8533	0.4577	0.8533	0.9238
No log	4.0	164	0.8283	0.4577	0.8283	0.9101
No log	4.0488	166	0.8002	0.4878	0.8002	0.8946
No log	4.0976	168	0.7304	0.5821	0.7304	0.8546
No log	4.1463	170	0.6859	0.5821	0.6859	0.8282
No log	4.1951	172	0.5663	0.6769	0.5663	0.7525
No log	4.2439	174	0.5212	0.6769	0.5212	0.7220
No log	4.2927	176	0.4770	0.6980	0.4770	0.6907
No log	4.3415	178	0.5156	0.7072	0.5156	0.7181
No log	4.3902	180	0.5498	0.5914	0.5498	0.7415
No log	4.4390	182	0.6819	0.5821	0.6819	0.8258
No log	4.4878	184	0.7042	0.5821	0.7042	0.8392
No log	4.5366	186	0.5638	0.6016	0.5638	0.7508
No log	4.5854	188	0.5212	0.6224	0.5212	0.7220
No log	4.6341	190	0.5486	0.6224	0.5486	0.7407
No log	4.6829	192	0.6139	0.5692	0.6139	0.7835
No log	4.7317	194	0.6556	0.5035	0.6556	0.8097
No log	4.7805	196	0.6710	0.5035	0.6710	0.8192
No log	4.8293	198	0.5876	0.5882	0.5876	0.7665
No log	4.8780	200	0.5360	0.6224	0.5360	0.7321
No log	4.9268	202	0.5387	0.6224	0.5387	0.7339
No log	4.9756	204	0.6112	0.6237	0.6112	0.7818
No log	5.0244	206	0.8180	0.5778	0.8180	0.9044
No log	5.0732	208	0.9313	0.5449	0.9313	0.9650
No log	5.1220	210	0.9145	0.5513	0.9145	0.9563
No log	5.1707	212	0.7637	0.5882	0.7637	0.8739
No log	5.2195	214	0.5060	0.7354	0.5060	0.7113
No log	5.2683	216	0.4221	0.7586	0.4221	0.6497
No log	5.3171	218	0.4202	0.7586	0.4202	0.6483
No log	5.3659	220	0.4837	0.7529	0.4837	0.6955
No log	5.4146	222	0.5805	0.6597	0.5805	0.7619
No log	5.4634	224	0.6444	0.6689	0.6444	0.8027
No log	5.5122	226	0.6729	0.6383	0.6729	0.8203
No log	5.5610	228	0.5400	0.7354	0.5400	0.7349
No log	5.6098	230	0.5095	0.7219	0.5095	0.7138
No log	5.6585	232	0.6133	0.6839	0.6133	0.7832
No log	5.7073	234	0.6201	0.6839	0.6201	0.7874
No log	5.7561	236	0.5260	0.7220	0.5260	0.7253
No log	5.8049	238	0.4447	0.7220	0.4447	0.6669
No log	5.8537	240	0.4408	0.7368	0.4408	0.6639
No log	5.9024	242	0.5477	0.6645	0.5477	0.7401
No log	5.9512	244	0.7013	0.6293	0.7013	0.8375
No log	6.0	246	0.8039	0.5882	0.8039	0.8966
No log	6.0488	248	0.7909	0.5778	0.7909	0.8893
No log	6.0976	250	0.7492	0.5778	0.7492	0.8656
No log	6.1463	252	0.6162	0.6423	0.6162	0.7850
No log	6.1951	254	0.5339	0.6423	0.5339	0.7307
No log	6.2439	256	0.5177	0.6423	0.5177	0.7195
No log	6.2927	258	0.5649	0.6316	0.5649	0.7516
No log	6.3415	260	0.5437	0.6316	0.5437	0.7374
No log	6.3902	262	0.5218	0.6316	0.5218	0.7224
No log	6.4390	264	0.5542	0.6316	0.5542	0.7444
No log	6.4878	266	0.6079	0.6387	0.6079	0.7797
No log	6.5366	268	0.5917	0.6387	0.5917	0.7692
No log	6.5854	270	0.6170	0.6316	0.6170	0.7855
No log	6.6341	272	0.5852	0.6316	0.5852	0.7650
No log	6.6829	274	0.5165	0.7619	0.5165	0.7187
No log	6.7317	276	0.5454	0.6957	0.5454	0.7385
No log	6.7805	278	0.6016	0.6293	0.6016	0.7757
No log	6.8293	280	0.6050	0.6293	0.6050	0.7778
No log	6.8780	282	0.5639	0.6934	0.5639	0.7509
No log	6.9268	284	0.5440	0.7308	0.5440	0.7376
No log	6.9756	286	0.5174	0.7368	0.5174	0.7193
No log	7.0244	288	0.4410	0.7529	0.4410	0.6641
No log	7.0732	290	0.3950	0.7941	0.3950	0.6285
No log	7.1220	292	0.3820	0.7941	0.3820	0.6181
No log	7.1707	294	0.3910	0.7941	0.3910	0.6253
No log	7.2195	296	0.4101	0.7941	0.4101	0.6404
No log	7.2683	298	0.4423	0.7529	0.4423	0.6651
No log	7.3171	300	0.4671	0.7529	0.4671	0.6835
No log	7.3659	302	0.5308	0.7072	0.5308	0.7286
No log	7.4146	304	0.6123	0.6237	0.6123	0.7825
No log	7.4634	306	0.6190	0.6028	0.6190	0.7867
No log	7.5122	308	0.5570	0.6125	0.5570	0.7463
No log	7.5610	310	0.4803	0.7368	0.4803	0.6931
No log	7.6098	312	0.4436	0.7941	0.4436	0.6660
No log	7.6585	314	0.4578	0.7941	0.4578	0.6766
No log	7.7073	316	0.5127	0.7220	0.5127	0.7160
No log	7.7561	318	0.6180	0.6125	0.6180	0.7861
No log	7.8049	320	0.7368	0.5655	0.7368	0.8584
No log	7.8537	322	0.8111	0.5471	0.8111	0.9006
No log	7.9024	324	0.8427	0.5471	0.8427	0.9180
No log	7.9512	326	0.7800	0.5471	0.7800	0.8832
No log	8.0	328	0.6604	0.6237	0.6604	0.8126
No log	8.0488	330	0.5412	0.6667	0.5412	0.7357
No log	8.0976	332	0.4819	0.7941	0.4819	0.6942
No log	8.1463	334	0.4363	0.7941	0.4363	0.6605
No log	8.1951	336	0.4285	0.7941	0.4285	0.6546
No log	8.2439	338	0.4419	0.7941	0.4419	0.6648
No log	8.2927	340	0.4846	0.7138	0.4846	0.6961
No log	8.3415	342	0.5637	0.6316	0.5637	0.7508
No log	8.3902	344	0.6461	0.6416	0.6461	0.8038
No log	8.4390	346	0.6778	0.5778	0.6778	0.8233
No log	8.4878	348	0.6518	0.6416	0.6518	0.8074
No log	8.5366	350	0.5924	0.6343	0.5924	0.7697
No log	8.5854	352	0.5321	0.6667	0.5321	0.7294
No log	8.6341	354	0.4906	0.7529	0.4906	0.7004
No log	8.6829	356	0.4623	0.7941	0.4623	0.6799
No log	8.7317	358	0.4611	0.7941	0.4611	0.6790
No log	8.7805	360	0.4774	0.7941	0.4774	0.6910
No log	8.8293	362	0.5094	0.7529	0.5094	0.7137
No log	8.8780	364	0.5515	0.6540	0.5515	0.7426
No log	8.9268	366	0.5723	0.6423	0.5723	0.7565
No log	8.9756	368	0.5907	0.6125	0.5907	0.7686
No log	9.0244	370	0.5916	0.6125	0.5916	0.7691
No log	9.0732	372	0.5661	0.6423	0.5661	0.7524
No log	9.1220	374	0.5328	0.6667	0.5328	0.7299
No log	9.1707	376	0.5112	0.7529	0.5112	0.7150
No log	9.2195	378	0.4969	0.7529	0.4969	0.7049
No log	9.2683	380	0.4862	0.7941	0.4862	0.6973
No log	9.3171	382	0.4791	0.7941	0.4791	0.6922
No log	9.3659	384	0.4731	0.7941	0.4731	0.6878
No log	9.4146	386	0.4747	0.7941	0.4747	0.6890
No log	9.4634	388	0.4880	0.7529	0.4880	0.6986
No log	9.5122	390	0.4985	0.7529	0.4985	0.7060
No log	9.5610	392	0.5039	0.6667	0.5039	0.7099
No log	9.6098	394	0.5042	0.6667	0.5042	0.7101
No log	9.6585	396	0.5028	0.6667	0.5028	0.7091
No log	9.7073	398	0.5020	0.6667	0.5020	0.7085
No log	9.7561	400	0.5070	0.6667	0.5070	0.7120
No log	9.8049	402	0.5103	0.6667	0.5103	0.7143
No log	9.8537	404	0.5137	0.6667	0.5137	0.7168
No log	9.9024	406	0.5168	0.6667	0.5168	0.7189
No log	9.9512	408	0.5198	0.6667	0.5198	0.7210
No log	10.0	410	0.5210	0.6667	0.5210	0.7218

Framework versions

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