ArabicNewSplits5_FineTuningAraBERT_run1_AugV5_k6_task1_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: 0.6119
• Qwk: 0.7514
• Mse: 0.6119
• Rmse: 0.7822

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	0.0513	2	5.0170	-0.0123	5.0170	2.2399
No log	0.1026	4	2.7977	0.1074	2.7977	1.6726
No log	0.1538	6	1.7189	0.0950	1.7189	1.3111
No log	0.2051	8	1.3453	0.1933	1.3453	1.1599
No log	0.2564	10	1.1566	0.3146	1.1566	1.0754
No log	0.3077	12	1.1661	0.2532	1.1661	1.0799
No log	0.3590	14	1.2082	0.2484	1.2082	1.0992
No log	0.4103	16	1.2023	0.2412	1.2023	1.0965
No log	0.4615	18	1.2248	0.2847	1.2248	1.1067
No log	0.5128	20	1.4693	0.2808	1.4693	1.2121
No log	0.5641	22	2.0479	0.1820	2.0479	1.4311
No log	0.6154	24	1.8770	0.2216	1.8770	1.3700
No log	0.6667	26	1.3455	0.2653	1.3455	1.1600
No log	0.7179	28	1.1498	0.3422	1.1498	1.0723
No log	0.7692	30	1.0841	0.3993	1.0841	1.0412
No log	0.8205	32	1.0078	0.4401	1.0078	1.0039
No log	0.8718	34	1.2305	0.3850	1.2305	1.1093
No log	0.9231	36	1.9015	0.2630	1.9015	1.3789
No log	0.9744	38	2.7816	0.1715	2.7816	1.6678
No log	1.0256	40	3.0096	0.1302	3.0096	1.7348
No log	1.0769	42	2.6384	0.2064	2.6384	1.6243
No log	1.1282	44	1.9743	0.2777	1.9743	1.4051
No log	1.1795	46	1.1186	0.4882	1.1186	1.0577
No log	1.2308	48	0.8609	0.5379	0.8609	0.9278
No log	1.2821	50	0.8520	0.5271	0.8520	0.9230
No log	1.3333	52	1.0300	0.5183	1.0300	1.0149
No log	1.3846	54	1.1754	0.5021	1.1754	1.0842
No log	1.4359	56	1.2368	0.5204	1.2368	1.1121
No log	1.4872	58	1.2287	0.5268	1.2287	1.1085
No log	1.5385	60	1.1725	0.5143	1.1725	1.0828
No log	1.5897	62	0.9493	0.5989	0.9493	0.9743
No log	1.6410	64	1.1310	0.4801	1.1310	1.0635
No log	1.6923	66	1.3073	0.2793	1.3073	1.1434
No log	1.7436	68	1.0276	0.5188	1.0276	1.0137
No log	1.7949	70	0.6716	0.7007	0.6716	0.8195
No log	1.8462	72	1.0144	0.5579	1.0144	1.0072
No log	1.8974	74	1.8688	0.2974	1.8688	1.3670
No log	1.9487	76	1.9641	0.3058	1.9641	1.4014
No log	2.0	78	1.6020	0.3330	1.6020	1.2657
No log	2.0513	80	1.0150	0.5533	1.0150	1.0075
No log	2.1026	82	0.7209	0.6608	0.7209	0.8491
No log	2.1538	84	0.6822	0.6851	0.6822	0.8259
No log	2.2051	86	0.7332	0.6867	0.7332	0.8563
No log	2.2564	88	0.9846	0.5944	0.9846	0.9923
No log	2.3077	90	1.1259	0.5735	1.1259	1.0611
No log	2.3590	92	1.0947	0.5622	1.0947	1.0463
No log	2.4103	94	0.9801	0.6076	0.9801	0.9900
No log	2.4615	96	0.9443	0.6072	0.9443	0.9717
No log	2.5128	98	1.0172	0.5597	1.0172	1.0085
No log	2.5641	100	1.0937	0.5039	1.0937	1.0458
No log	2.6154	102	1.2595	0.5035	1.2595	1.1223
No log	2.6667	104	1.2615	0.4876	1.2615	1.1232
No log	2.7179	106	1.1358	0.4766	1.1358	1.0657
No log	2.7692	108	1.0018	0.5531	1.0018	1.0009
No log	2.8205	110	0.7332	0.6385	0.7332	0.8563
No log	2.8718	112	0.5864	0.7073	0.5864	0.7658
No log	2.9231	114	0.6033	0.7471	0.6033	0.7767
No log	2.9744	116	0.6157	0.7705	0.6157	0.7847
No log	3.0256	118	0.6208	0.7375	0.6208	0.7879
No log	3.0769	120	0.6644	0.7581	0.6644	0.8151
No log	3.1282	122	0.7185	0.7459	0.7185	0.8477
No log	3.1795	124	0.6820	0.7436	0.6820	0.8259
No log	3.2308	126	0.6586	0.7104	0.6586	0.8115
No log	3.2821	128	0.8657	0.6862	0.8657	0.9304
No log	3.3333	130	1.2241	0.5510	1.2241	1.1064
No log	3.3846	132	1.2647	0.5214	1.2647	1.1246
No log	3.4359	134	1.0622	0.6015	1.0622	1.0307
No log	3.4872	136	0.7350	0.6903	0.7350	0.8573
No log	3.5385	138	0.5846	0.7123	0.5846	0.7646
No log	3.5897	140	0.6455	0.6987	0.6455	0.8034
No log	3.6410	142	0.6246	0.6917	0.6246	0.7903
No log	3.6923	144	0.5753	0.7247	0.5753	0.7585
No log	3.7436	146	0.6288	0.6950	0.6288	0.7930
No log	3.7949	148	0.7532	0.6189	0.7532	0.8679
No log	3.8462	150	0.7666	0.6183	0.7666	0.8755
No log	3.8974	152	0.6667	0.6742	0.6667	0.8165
No log	3.9487	154	0.6048	0.6891	0.6048	0.7777
No log	4.0	156	0.6064	0.7155	0.6064	0.7787
No log	4.0513	158	0.6403	0.7176	0.6403	0.8002
No log	4.1026	160	0.7801	0.6737	0.7801	0.8832
No log	4.1538	162	0.8790	0.6766	0.8790	0.9375
No log	4.2051	164	0.8738	0.6721	0.8738	0.9348
No log	4.2564	166	0.7566	0.6866	0.7566	0.8698
No log	4.3077	168	0.7076	0.6959	0.7076	0.8412
No log	4.3590	170	0.7195	0.6866	0.7195	0.8483
No log	4.4103	172	0.7485	0.6878	0.7485	0.8652
No log	4.4615	174	0.7059	0.6925	0.7059	0.8402
No log	4.5128	176	0.7276	0.6615	0.7276	0.8530
No log	4.5641	178	0.7036	0.6865	0.7036	0.8388
No log	4.6154	180	0.6817	0.6827	0.6817	0.8257
No log	4.6667	182	0.6683	0.7061	0.6683	0.8175
No log	4.7179	184	0.6557	0.7252	0.6557	0.8097
No log	4.7692	186	0.6709	0.7228	0.6709	0.8191
No log	4.8205	188	0.7128	0.6990	0.7128	0.8443
No log	4.8718	190	0.6837	0.7188	0.6837	0.8269
No log	4.9231	192	0.6883	0.7082	0.6883	0.8296
No log	4.9744	194	0.7365	0.6974	0.7365	0.8582
No log	5.0256	196	0.7031	0.7130	0.7031	0.8385
No log	5.0769	198	0.6709	0.7108	0.6709	0.8191
No log	5.1282	200	0.6725	0.6942	0.6725	0.8201
No log	5.1795	202	0.6926	0.7071	0.6926	0.8322
No log	5.2308	204	0.7347	0.7030	0.7347	0.8572
No log	5.2821	206	0.7252	0.7071	0.7252	0.8516
No log	5.3333	208	0.7522	0.7017	0.7522	0.8673
No log	5.3846	210	0.7223	0.7067	0.7223	0.8499
No log	5.4359	212	0.6866	0.6997	0.6866	0.8286
No log	5.4872	214	0.6401	0.7156	0.6401	0.8000
No log	5.5385	216	0.6225	0.7412	0.6225	0.7890
No log	5.5897	218	0.6196	0.7286	0.6196	0.7871
No log	5.6410	220	0.6424	0.7180	0.6424	0.8015
No log	5.6923	222	0.6651	0.7172	0.6651	0.8155
No log	5.7436	224	0.7140	0.6874	0.7140	0.8450
No log	5.7949	226	0.7476	0.6687	0.7476	0.8646
No log	5.8462	228	0.7961	0.6567	0.7961	0.8922
No log	5.8974	230	0.8782	0.6600	0.8782	0.9371
No log	5.9487	232	0.8136	0.6596	0.8136	0.9020
No log	6.0	234	0.7024	0.7078	0.7024	0.8381
No log	6.0513	236	0.6456	0.7263	0.6456	0.8035
No log	6.1026	238	0.6378	0.7470	0.6378	0.7986
No log	6.1538	240	0.6285	0.7560	0.6285	0.7927
No log	6.2051	242	0.6186	0.7599	0.6186	0.7865
No log	6.2564	244	0.6288	0.7217	0.6288	0.7929
No log	6.3077	246	0.6298	0.7221	0.6298	0.7936
No log	6.3590	248	0.6166	0.7368	0.6166	0.7853
No log	6.4103	250	0.5986	0.7601	0.5986	0.7737
No log	6.4615	252	0.6018	0.7601	0.6018	0.7757
No log	6.5128	254	0.6059	0.7529	0.6059	0.7784
No log	6.5641	256	0.6010	0.7713	0.6010	0.7752
No log	6.6154	258	0.6072	0.7502	0.6072	0.7792
No log	6.6667	260	0.6222	0.7474	0.6222	0.7888
No log	6.7179	262	0.6298	0.7326	0.6298	0.7936
No log	6.7692	264	0.6237	0.7474	0.6237	0.7898
No log	6.8205	266	0.6161	0.7405	0.6161	0.7849
No log	6.8718	268	0.6096	0.7468	0.6096	0.7808
No log	6.9231	270	0.6127	0.7407	0.6127	0.7827
No log	6.9744	272	0.6160	0.7590	0.6160	0.7849
No log	7.0256	274	0.6096	0.7454	0.6096	0.7808
No log	7.0769	276	0.6063	0.7454	0.6063	0.7786
No log	7.1282	278	0.6106	0.7495	0.6106	0.7814
No log	7.1795	280	0.6416	0.7148	0.6416	0.8010
No log	7.2308	282	0.6952	0.6881	0.6952	0.8338
No log	7.2821	284	0.7033	0.6781	0.7033	0.8386
No log	7.3333	286	0.6852	0.6874	0.6852	0.8278
No log	7.3846	288	0.6529	0.7004	0.6529	0.8080
No log	7.4359	290	0.6135	0.7332	0.6135	0.7833
No log	7.4872	292	0.6023	0.7501	0.6023	0.7761
No log	7.5385	294	0.6072	0.7637	0.6072	0.7792
No log	7.5897	296	0.6163	0.7519	0.6163	0.7850
No log	7.6410	298	0.6196	0.7434	0.6196	0.7872
No log	7.6923	300	0.6309	0.7568	0.6309	0.7943
No log	7.7436	302	0.6443	0.7371	0.6443	0.8027
No log	7.7949	304	0.6454	0.7386	0.6454	0.8034
No log	7.8462	306	0.6372	0.7487	0.6372	0.7982
No log	7.8974	308	0.6302	0.7344	0.6302	0.7938
No log	7.9487	310	0.6280	0.7359	0.6280	0.7925
No log	8.0	312	0.6262	0.7344	0.6262	0.7913
No log	8.0513	314	0.6304	0.7423	0.6304	0.7940
No log	8.1026	316	0.6412	0.7445	0.6412	0.8008
No log	8.1538	318	0.6468	0.7274	0.6468	0.8042
No log	8.2051	320	0.6521	0.7274	0.6521	0.8075
No log	8.2564	322	0.6638	0.7125	0.6638	0.8147
No log	8.3077	324	0.6608	0.7125	0.6608	0.8129
No log	8.3590	326	0.6478	0.7254	0.6478	0.8049
No log	8.4103	328	0.6312	0.7550	0.6312	0.7945
No log	8.4615	330	0.6233	0.7505	0.6233	0.7895
No log	8.5128	332	0.6312	0.7514	0.6312	0.7945
No log	8.5641	334	0.6494	0.7044	0.6494	0.8059
No log	8.6154	336	0.6626	0.7109	0.6626	0.8140
No log	8.6667	338	0.6535	0.7109	0.6535	0.8084
No log	8.7179	340	0.6349	0.7136	0.6349	0.7968
No log	8.7692	342	0.6159	0.7217	0.6159	0.7848
No log	8.8205	344	0.6033	0.7482	0.6033	0.7767
No log	8.8718	346	0.6049	0.7630	0.6049	0.7777
No log	8.9231	348	0.6130	0.7523	0.6130	0.7830
No log	8.9744	350	0.6274	0.7505	0.6274	0.7921
No log	9.0256	352	0.6364	0.7410	0.6364	0.7977
No log	9.0769	354	0.6369	0.7505	0.6369	0.7981
No log	9.1282	356	0.6315	0.7505	0.6315	0.7947
No log	9.1795	358	0.6231	0.7505	0.6231	0.7893
No log	9.2308	360	0.6160	0.7537	0.6160	0.7849
No log	9.2821	362	0.6134	0.7404	0.6134	0.7832
No log	9.3333	364	0.6131	0.7505	0.6131	0.7830
No log	9.3846	366	0.6145	0.7480	0.6145	0.7839
No log	9.4359	368	0.6160	0.7514	0.6160	0.7848
No log	9.4872	370	0.6173	0.7471	0.6173	0.7857
No log	9.5385	372	0.6173	0.7407	0.6173	0.7857
No log	9.5897	374	0.6168	0.7407	0.6168	0.7854
No log	9.6410	376	0.6160	0.7407	0.6160	0.7849
No log	9.6923	378	0.6149	0.7407	0.6149	0.7842
No log	9.7436	380	0.6143	0.7407	0.6143	0.7838
No log	9.7949	382	0.6136	0.7407	0.6136	0.7833
No log	9.8462	384	0.6130	0.7471	0.6130	0.7829
No log	9.8974	386	0.6123	0.7514	0.6123	0.7825
No log	9.9487	388	0.6120	0.7514	0.6120	0.7823
No log	10.0	390	0.6119	0.7514	0.6119	0.7822

Framework versions

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