ArabicNewSplits5_FineTuningAraBERT_run2_AugV5_k5_task3_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: 0.8622
• Qwk: 0.2381
• Mse: 0.8622
• Rmse: 0.9285

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	0.0645	2	3.2191	-0.0138	3.2191	1.7942
No log	0.1290	4	1.7386	-0.0070	1.7386	1.3186
No log	0.1935	6	1.1691	0.0294	1.1691	1.0813
No log	0.2581	8	1.2552	0.0	1.2552	1.1203
No log	0.3226	10	1.3894	0.0	1.3894	1.1787
No log	0.3871	12	1.1443	0.0	1.1443	1.0697
No log	0.4516	14	1.0472	0.0	1.0472	1.0233
No log	0.5161	16	0.7757	-0.0547	0.7757	0.8807
No log	0.5806	18	0.7600	0.0359	0.7600	0.8718
No log	0.6452	20	0.8267	0.0991	0.8267	0.9092
No log	0.7097	22	0.8137	0.1111	0.8137	0.9020
No log	0.7742	24	0.9318	0.0201	0.9318	0.9653
No log	0.8387	26	0.8773	0.0380	0.8773	0.9366
No log	0.9032	28	0.8646	0.0526	0.8646	0.9298
No log	0.9677	30	0.8028	-0.1073	0.8028	0.8960
No log	1.0323	32	0.8444	-0.1217	0.8444	0.9189
No log	1.0968	34	0.9526	0.0617	0.9526	0.9760
No log	1.1613	36	1.1076	0.0388	1.1076	1.0524
No log	1.2258	38	1.0864	0.0345	1.0864	1.0423
No log	1.2903	40	0.8545	0.0717	0.8545	0.9244
No log	1.3548	42	0.7772	0.0857	0.7772	0.8816
No log	1.4194	44	0.6910	0.0256	0.6910	0.8312
No log	1.4839	46	0.6457	0.0400	0.6457	0.8035
No log	1.5484	48	0.6853	0.0061	0.6853	0.8278
No log	1.6129	50	0.7348	0.0877	0.7348	0.8572
No log	1.6774	52	1.0232	0.2397	1.0232	1.0115
No log	1.7419	54	0.8267	0.1691	0.8267	0.9092
No log	1.8065	56	0.6346	0.0222	0.6346	0.7966
No log	1.8710	58	0.6989	-0.1515	0.6989	0.8360
No log	1.9355	60	0.6905	-0.1473	0.6905	0.8310
No log	2.0	62	0.6234	-0.1556	0.6234	0.7896
No log	2.0645	64	0.7015	0.2258	0.7015	0.8375
No log	2.1290	66	1.3157	0.0903	1.3157	1.1471
No log	2.1935	68	1.3669	0.0614	1.3669	1.1691
No log	2.2581	70	0.9912	0.2066	0.9912	0.9956
No log	2.3226	72	0.6649	0.2593	0.6649	0.8154
No log	2.3871	74	0.5977	0.1707	0.5977	0.7731
No log	2.4516	76	0.6064	0.2105	0.6064	0.7787
No log	2.5161	78	0.6180	0.1902	0.6180	0.7861
No log	2.5806	80	0.6577	0.2000	0.6577	0.8110
No log	2.6452	82	0.7030	0.2323	0.7030	0.8385
No log	2.7097	84	0.7140	0.2340	0.7140	0.8450
No log	2.7742	86	0.7482	0.2086	0.7482	0.8650
No log	2.8387	88	0.7046	0.3433	0.7046	0.8394
No log	2.9032	90	0.8478	0.2000	0.8478	0.9208
No log	2.9677	92	0.9828	0.2527	0.9828	0.9914
No log	3.0323	94	0.6721	0.2579	0.6721	0.8198
No log	3.0968	96	0.5711	0.3161	0.5711	0.7557
No log	3.1613	98	0.5300	0.3043	0.5300	0.7280
No log	3.2258	100	0.5343	0.3231	0.5343	0.7309
No log	3.2903	102	0.5304	0.3433	0.5304	0.7283
No log	3.3548	104	0.5680	0.3905	0.5680	0.7537
No log	3.4194	106	0.8299	0.1858	0.8299	0.9110
No log	3.4839	108	0.9447	0.0988	0.9447	0.9719
No log	3.5484	110	0.9173	0.0894	0.9173	0.9578
No log	3.6129	112	0.7026	0.2709	0.7026	0.8382
No log	3.6774	114	0.6845	0.28	0.6845	0.8273
No log	3.7419	116	0.8811	0.1724	0.8811	0.9387
No log	3.8065	118	0.7490	0.1925	0.7490	0.8654
No log	3.8710	120	0.6530	0.3118	0.6530	0.8081
No log	3.9355	122	0.8656	0.0151	0.8656	0.9304
No log	4.0	124	0.9055	-0.0196	0.9055	0.9516
No log	4.0645	126	0.7687	0.0497	0.7687	0.8767
No log	4.1290	128	0.6164	0.3623	0.6164	0.7851
No log	4.1935	130	0.6102	0.3398	0.6102	0.7811
No log	4.2581	132	0.6261	0.3665	0.6261	0.7913
No log	4.3226	134	0.7310	0.3271	0.7310	0.8550
No log	4.3871	136	0.6670	0.3116	0.6670	0.8167
No log	4.4516	138	0.6782	0.3208	0.6782	0.8236
No log	4.5161	140	0.7597	0.3303	0.7597	0.8716
No log	4.5806	142	0.8625	0.1730	0.8625	0.9287
No log	4.6452	144	1.1424	0.0747	1.1424	1.0688
No log	4.7097	146	1.2341	0.0435	1.2341	1.1109
No log	4.7742	148	1.2610	0.0183	1.2610	1.1230
No log	4.8387	150	1.0460	0.0598	1.0460	1.0228
No log	4.9032	152	0.7827	0.2137	0.7827	0.8847
No log	4.9677	154	0.6576	0.2593	0.6576	0.8109
No log	5.0323	156	0.6680	0.2566	0.6680	0.8173
No log	5.0968	158	0.8516	0.1319	0.8516	0.9228
No log	5.1613	160	1.1343	0.0625	1.1343	1.0650
No log	5.2258	162	1.3731	0.0363	1.3731	1.1718
No log	5.2903	164	1.4313	0.0872	1.4313	1.1964
No log	5.3548	166	1.4155	0.0627	1.4155	1.1897
No log	5.4194	168	1.0556	0.1278	1.0556	1.0274
No log	5.4839	170	0.9361	0.1571	0.9361	0.9675
No log	5.5484	172	0.9951	0.1278	0.9951	0.9975
No log	5.6129	174	0.9991	0.1571	0.9991	0.9995
No log	5.6774	176	0.8773	0.2698	0.8773	0.9366
No log	5.7419	178	0.9063	0.2199	0.9063	0.9520
No log	5.8065	180	0.9946	0.1571	0.9946	0.9973
No log	5.8710	182	1.1448	0.1032	1.1448	1.0700
No log	5.9355	184	1.1738	0.1049	1.1738	1.0834
No log	6.0	186	0.8733	0.3255	0.8733	0.9345
No log	6.0645	188	0.7111	0.3770	0.7111	0.8433
No log	6.1290	190	0.6335	0.4386	0.6335	0.7959
No log	6.1935	192	0.6354	0.4678	0.6354	0.7971
No log	6.2581	194	0.6568	0.4050	0.6568	0.8104
No log	6.3226	196	0.8086	0.2868	0.8086	0.8992
No log	6.3871	198	0.9190	0.2062	0.9190	0.9587
No log	6.4516	200	0.8817	0.2062	0.8817	0.9390
No log	6.5161	202	0.7728	0.3613	0.7728	0.8791
No log	6.5806	204	0.6828	0.3846	0.6828	0.8263
No log	6.6452	206	0.6678	0.3571	0.6678	0.8172
No log	6.7097	208	0.7621	0.3613	0.7621	0.8730
No log	6.7742	210	0.8866	0.2698	0.8866	0.9416
No log	6.8387	212	0.8307	0.3333	0.8307	0.9114
No log	6.9032	214	0.8584	0.3306	0.8584	0.9265
No log	6.9677	216	0.9693	0.1562	0.9693	0.9845
No log	7.0323	218	1.0275	0.1264	1.0275	1.0136
No log	7.0968	220	0.9542	0.1818	0.9542	0.9768
No log	7.1613	222	0.8374	0.3333	0.8374	0.9151
No log	7.2258	224	0.7137	0.3665	0.7137	0.8448
No log	7.2903	226	0.6331	0.3665	0.6331	0.7957
No log	7.3548	228	0.6287	0.3333	0.6287	0.7929
No log	7.4194	230	0.6557	0.3761	0.6557	0.8097
No log	7.4839	232	0.7239	0.3665	0.7239	0.8508
No log	7.5484	234	0.7617	0.3684	0.7617	0.8728
No log	7.6129	236	0.8016	0.3153	0.8016	0.8953
No log	7.6774	238	0.7892	0.3422	0.7892	0.8883
No log	7.7419	240	0.7996	0.2511	0.7996	0.8942
No log	7.8065	242	0.7647	0.2982	0.7647	0.8745
No log	7.8710	244	0.7866	0.2793	0.7866	0.8869
No log	7.9355	246	0.8470	0.2137	0.8470	0.9203
No log	8.0	248	0.9113	0.1811	0.9113	0.9546
No log	8.0645	250	0.8883	0.2459	0.8883	0.9425
No log	8.1290	252	0.7801	0.3128	0.7801	0.8833
No log	8.1935	254	0.6758	0.3719	0.6758	0.8221
No log	8.2581	256	0.6379	0.4133	0.6379	0.7987
No log	8.3226	258	0.6506	0.4435	0.6506	0.8066
No log	8.3871	260	0.6714	0.4240	0.6714	0.8194
No log	8.4516	262	0.7337	0.3719	0.7337	0.8565
No log	8.5161	264	0.8042	0.4043	0.8042	0.8968
No log	8.5806	266	0.8765	0.2126	0.8765	0.9362
No log	8.6452	268	0.9347	0.1571	0.9347	0.9668
No log	8.7097	270	0.9328	0.1571	0.9328	0.9658
No log	8.7742	272	0.9070	0.1875	0.9070	0.9524
No log	8.8387	274	0.8560	0.2131	0.8560	0.9252
No log	8.9032	276	0.7888	0.4	0.7888	0.8881
No log	8.9677	278	0.7244	0.3613	0.7244	0.8511
No log	9.0323	280	0.6783	0.4093	0.6783	0.8236
No log	9.0968	282	0.6781	0.4093	0.6781	0.8235
No log	9.1613	284	0.7127	0.4050	0.7127	0.8442
No log	9.2258	286	0.7631	0.3613	0.7631	0.8735
No log	9.2903	288	0.8085	0.2922	0.8085	0.8992
No log	9.3548	290	0.8356	0.2569	0.8356	0.9141
No log	9.4194	292	0.8635	0.2941	0.8635	0.9292
No log	9.4839	294	0.8569	0.2941	0.8569	0.9257
No log	9.5484	296	0.8476	0.2941	0.8476	0.9206
No log	9.6129	298	0.8472	0.2960	0.8472	0.9205
No log	9.6774	300	0.8486	0.2960	0.8486	0.9212
No log	9.7419	302	0.8469	0.2960	0.8469	0.9202
No log	9.8065	304	0.8515	0.2960	0.8515	0.9228
No log	9.8710	306	0.8552	0.2941	0.8552	0.9248
No log	9.9355	308	0.8594	0.2381	0.8594	0.9270
No log	10.0	310	0.8622	0.2381	0.8622	0.9285

Framework versions

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