ArabicNewSplits6_FineTuningAraBERT_run1_AugV5_k7_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: 0.6453
• Qwk: 0.7325
• Mse: 0.6453
• Rmse: 0.8033

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	0.0556	2	5.0303	-0.0009	5.0303	2.2428
No log	0.1111	4	2.9418	0.0925	2.9418	1.7152
No log	0.1667	6	1.7744	0.0499	1.7744	1.3321
No log	0.2222	8	1.4064	0.2107	1.4064	1.1859
No log	0.2778	10	1.2355	0.1486	1.2355	1.1115
No log	0.3333	12	1.4424	0.0749	1.4424	1.2010
No log	0.3889	14	1.5696	-0.0236	1.5696	1.2528
No log	0.4444	16	1.6963	-0.0582	1.6963	1.3024
No log	0.5	18	1.9663	0.0273	1.9663	1.4022
No log	0.5556	20	1.9777	0.0388	1.9777	1.4063
No log	0.6111	22	1.6961	0.0021	1.6961	1.3024
No log	0.6667	24	1.2241	0.3356	1.2241	1.1064
No log	0.7222	26	1.1686	0.2740	1.1686	1.0810
No log	0.7778	28	1.1604	0.3779	1.1604	1.0772
No log	0.8333	30	1.2766	0.2036	1.2766	1.1299
No log	0.8889	32	1.4619	0.1705	1.4619	1.2091
No log	0.9444	34	1.6379	0.1732	1.6379	1.2798
No log	1.0	36	1.7565	0.1606	1.7565	1.3253
No log	1.0556	38	1.5053	0.2132	1.5053	1.2269
No log	1.1111	40	1.2234	0.2375	1.2234	1.1061
No log	1.1667	42	1.1060	0.3485	1.1060	1.0516
No log	1.2222	44	1.2044	0.3279	1.2044	1.0975
No log	1.2778	46	1.2941	0.3467	1.2941	1.1376
No log	1.3333	48	1.3319	0.3335	1.3319	1.1541
No log	1.3889	50	1.3596	0.3507	1.3596	1.1660
No log	1.4444	52	1.2819	0.3772	1.2819	1.1322
No log	1.5	54	1.0732	0.4313	1.0732	1.0360
No log	1.5556	56	0.9510	0.4711	0.9510	0.9752
No log	1.6111	58	1.0566	0.4323	1.0566	1.0279
No log	1.6667	60	1.3413	0.2533	1.3413	1.1581
No log	1.7222	62	1.3026	0.3097	1.3026	1.1413
No log	1.7778	64	1.0554	0.4399	1.0554	1.0273
No log	1.8333	66	0.9016	0.4504	0.9016	0.9495
No log	1.8889	68	0.8952	0.4317	0.8952	0.9462
No log	1.9444	70	0.8935	0.4403	0.8935	0.9452
No log	2.0	72	0.8927	0.4454	0.8927	0.9449
No log	2.0556	74	0.9208	0.4675	0.9208	0.9596
No log	2.1111	76	0.9029	0.4623	0.9029	0.9502
No log	2.1667	78	0.9408	0.4637	0.9408	0.9700
No log	2.2222	80	1.0190	0.4893	1.0190	1.0095
No log	2.2778	82	1.0671	0.4895	1.0671	1.0330
No log	2.3333	84	1.1786	0.4916	1.1786	1.0856
No log	2.3889	86	1.0193	0.5293	1.0193	1.0096
No log	2.4444	88	0.8010	0.5970	0.8010	0.8950
No log	2.5	90	0.7982	0.6436	0.7982	0.8934
No log	2.5556	92	0.7932	0.6624	0.7932	0.8906
No log	2.6111	94	0.8052	0.6312	0.8052	0.8973
No log	2.6667	96	0.8463	0.6333	0.8463	0.9199
No log	2.7222	98	0.7692	0.6627	0.7692	0.8771
No log	2.7778	100	0.8556	0.61	0.8556	0.9250
No log	2.8333	102	0.9316	0.5769	0.9316	0.9652
No log	2.8889	104	0.8645	0.6246	0.8645	0.9298
No log	2.9444	106	0.9404	0.5792	0.9404	0.9697
No log	3.0	108	0.9873	0.5682	0.9873	0.9936
No log	3.0556	110	0.9067	0.5902	0.9067	0.9522
No log	3.1111	112	0.8926	0.5953	0.8926	0.9448
No log	3.1667	114	0.8088	0.6367	0.8088	0.8994
No log	3.2222	116	0.7594	0.6609	0.7594	0.8715
No log	3.2778	118	0.8630	0.6495	0.8630	0.9290
No log	3.3333	120	1.1295	0.5136	1.1295	1.0628
No log	3.3889	122	1.2351	0.4974	1.2351	1.1114
No log	3.4444	124	1.0563	0.6020	1.0563	1.0278
No log	3.5	126	0.8236	0.6729	0.8236	0.9075
No log	3.5556	128	0.8266	0.6852	0.8266	0.9092
No log	3.6111	130	0.9408	0.6326	0.9408	0.9700
No log	3.6667	132	1.0728	0.5752	1.0728	1.0357
No log	3.7222	134	0.9849	0.6132	0.9849	0.9924
No log	3.7778	136	0.7696	0.6619	0.7696	0.8772
No log	3.8333	138	0.7392	0.6649	0.7392	0.8597
No log	3.8889	140	0.7542	0.6371	0.7542	0.8685
No log	3.9444	142	0.6822	0.6741	0.6822	0.8260
No log	4.0	144	0.6982	0.6620	0.6982	0.8356
No log	4.0556	146	0.6877	0.6874	0.6877	0.8293
No log	4.1111	148	0.6576	0.6750	0.6576	0.8109
No log	4.1667	150	0.6698	0.6817	0.6698	0.8184
No log	4.2222	152	0.6532	0.6590	0.6532	0.8082
No log	4.2778	154	0.7428	0.6912	0.7428	0.8619
No log	4.3333	156	0.9281	0.6621	0.9281	0.9634
No log	4.3889	158	0.8581	0.6561	0.8581	0.9263
No log	4.4444	160	0.6826	0.6676	0.6826	0.8262
No log	4.5	162	0.6505	0.6731	0.6505	0.8065
No log	4.5556	164	0.6463	0.6676	0.6463	0.8040
No log	4.6111	166	0.7657	0.6840	0.7657	0.8751
No log	4.6667	168	0.8280	0.6754	0.8280	0.9099
No log	4.7222	170	0.7497	0.7076	0.7497	0.8659
No log	4.7778	172	0.7483	0.7323	0.7483	0.8651
No log	4.8333	174	0.8170	0.6560	0.8170	0.9039
No log	4.8889	176	0.9383	0.6196	0.9383	0.9687
No log	4.9444	178	0.9518	0.6268	0.9518	0.9756
No log	5.0	180	0.9162	0.6367	0.9162	0.9572
No log	5.0556	182	0.8657	0.6432	0.8657	0.9304
No log	5.1111	184	0.7838	0.6629	0.7838	0.8853
No log	5.1667	186	0.8047	0.6699	0.8047	0.8970
No log	5.2222	188	0.9472	0.6400	0.9472	0.9733
No log	5.2778	190	0.9560	0.6275	0.9560	0.9778
No log	5.3333	192	0.8251	0.6678	0.8251	0.9084
No log	5.3889	194	0.7037	0.6812	0.7037	0.8389
No log	5.4444	196	0.6382	0.7161	0.6382	0.7988
No log	5.5	198	0.6264	0.7176	0.6264	0.7914
No log	5.5556	200	0.6843	0.7004	0.6843	0.8272
No log	5.6111	202	0.9505	0.6097	0.9505	0.9750
No log	5.6667	204	1.1471	0.5386	1.1471	1.0710
No log	5.7222	206	1.1045	0.5466	1.1045	1.0509
No log	5.7778	208	0.8768	0.6215	0.8768	0.9364
No log	5.8333	210	0.6366	0.7506	0.6366	0.7979
No log	5.8889	212	0.6312	0.6853	0.6312	0.7945
No log	5.9444	214	0.6528	0.6875	0.6528	0.8080
No log	6.0	216	0.6454	0.7222	0.6454	0.8033
No log	6.0556	218	0.7762	0.6990	0.7762	0.8810
No log	6.1111	220	1.0343	0.6061	1.0343	1.0170
No log	6.1667	222	1.1275	0.5806	1.1275	1.0618
No log	6.2222	224	1.0633	0.5893	1.0633	1.0312
No log	6.2778	226	0.9046	0.6088	0.9046	0.9511
No log	6.3333	228	0.7293	0.7008	0.7293	0.8540
No log	6.3889	230	0.6563	0.7033	0.6563	0.8101
No log	6.4444	232	0.6499	0.6891	0.6499	0.8062
No log	6.5	234	0.6499	0.6781	0.6499	0.8062
No log	6.5556	236	0.6904	0.7103	0.6904	0.8309
No log	6.6111	238	0.7647	0.6869	0.7647	0.8745
No log	6.6667	240	0.7647	0.6869	0.7647	0.8744
No log	6.7222	242	0.6996	0.7082	0.6996	0.8364
No log	6.7778	244	0.6475	0.6854	0.6475	0.8047
No log	6.8333	246	0.6354	0.6742	0.6354	0.7971
No log	6.8889	248	0.6383	0.6876	0.6383	0.7990
No log	6.9444	250	0.6485	0.6914	0.6485	0.8053
No log	7.0	252	0.6988	0.7047	0.6988	0.8359
No log	7.0556	254	0.7544	0.6890	0.7544	0.8686
No log	7.1111	256	0.7551	0.6890	0.7551	0.8690
No log	7.1667	258	0.7206	0.6988	0.7206	0.8489
No log	7.2222	260	0.6715	0.7164	0.6715	0.8194
No log	7.2778	262	0.6586	0.7133	0.6586	0.8115
No log	7.3333	264	0.6651	0.6941	0.6651	0.8156
No log	7.3889	266	0.7016	0.7012	0.7016	0.8376
No log	7.4444	268	0.7181	0.7031	0.7181	0.8474
No log	7.5	270	0.7028	0.7012	0.7028	0.8384
No log	7.5556	272	0.7121	0.7031	0.7121	0.8438
No log	7.6111	274	0.7171	0.6904	0.7171	0.8468
No log	7.6667	276	0.6935	0.6857	0.6935	0.8328
No log	7.7222	278	0.6548	0.6872	0.6548	0.8092
No log	7.7778	280	0.6461	0.7169	0.6461	0.8038
No log	7.8333	282	0.6629	0.6933	0.6629	0.8142
No log	7.8889	284	0.6594	0.6953	0.6594	0.8120
No log	7.9444	286	0.6470	0.6985	0.6470	0.8044
No log	8.0	288	0.6626	0.7009	0.6626	0.8140
No log	8.0556	290	0.7308	0.6817	0.7308	0.8549
No log	8.1111	292	0.7918	0.6585	0.7918	0.8899
No log	8.1667	294	0.8090	0.6531	0.8090	0.8995
No log	8.2222	296	0.7725	0.6698	0.7725	0.8789
No log	8.2778	298	0.7140	0.6937	0.7140	0.8450
No log	8.3333	300	0.6697	0.6674	0.6697	0.8183
No log	8.3889	302	0.6497	0.6838	0.6497	0.8060
No log	8.4444	304	0.6417	0.6901	0.6417	0.8011
No log	8.5	306	0.6415	0.6838	0.6415	0.8009
No log	8.5556	308	0.6476	0.6838	0.6476	0.8047
No log	8.6111	310	0.6583	0.6988	0.6583	0.8113
No log	8.6667	312	0.6703	0.6753	0.6703	0.8187
No log	8.7222	314	0.6706	0.6971	0.6706	0.8189
No log	8.7778	316	0.6724	0.7181	0.6724	0.8200
No log	8.8333	318	0.6837	0.7238	0.6837	0.8269
No log	8.8889	320	0.6926	0.7232	0.6926	0.8322
No log	8.9444	322	0.6943	0.7232	0.6943	0.8333
No log	9.0	324	0.7123	0.6923	0.7123	0.8440
No log	9.0556	326	0.7322	0.6961	0.7322	0.8557
No log	9.1111	328	0.7454	0.6773	0.7454	0.8634
No log	9.1667	330	0.7414	0.6773	0.7414	0.8610
No log	9.2222	332	0.7238	0.6876	0.7238	0.8508
No log	9.2778	334	0.7078	0.7006	0.7078	0.8413
No log	9.3333	336	0.6955	0.7300	0.6955	0.8340
No log	9.3889	338	0.6805	0.7160	0.6805	0.8249
No log	9.4444	340	0.6627	0.7130	0.6627	0.8141
No log	9.5	342	0.6546	0.7134	0.6546	0.8091
No log	9.5556	344	0.6471	0.7325	0.6471	0.8044
No log	9.6111	346	0.6416	0.6894	0.6416	0.8010
No log	9.6667	348	0.6389	0.6941	0.6389	0.7993
No log	9.7222	350	0.6397	0.6894	0.6397	0.7998
No log	9.7778	352	0.6417	0.7047	0.6417	0.8010
No log	9.8333	354	0.6439	0.7113	0.6439	0.8024
No log	9.8889	356	0.6450	0.7325	0.6450	0.8031
No log	9.9444	358	0.6452	0.7325	0.6452	0.8032
No log	10.0	360	0.6453	0.7325	0.6453	0.8033

Framework versions

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