ArabicNewSplits5_FineTuningAraBERT_run1_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: 1.0147
• Qwk: 0.2258
• Mse: 1.0147
• Rmse: 1.0073

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	3.4786	0.0039	3.4786	1.8651
No log	0.1290	4	2.9461	0.0303	2.9461	1.7164
No log	0.1935	6	1.1775	0.0	1.1775	1.0851
No log	0.2581	8	0.8793	0.0388	0.8793	0.9377
No log	0.3226	10	0.9149	-0.0233	0.9149	0.9565
No log	0.3871	12	0.9782	0.0038	0.9782	0.9891
No log	0.4516	14	0.6475	0.1206	0.6475	0.8047
No log	0.5161	16	0.5921	0.0476	0.5921	0.7695
No log	0.5806	18	0.7084	0.2821	0.7084	0.8417
No log	0.6452	20	1.8557	-0.0649	1.8557	1.3623
No log	0.7097	22	2.3325	0.0106	2.3325	1.5273
No log	0.7742	24	1.4644	0.0	1.4644	1.2101
No log	0.8387	26	1.0052	0.0	1.0052	1.0026
No log	0.9032	28	0.9136	0.0078	0.9136	0.9558
No log	0.9677	30	0.8180	0.0569	0.8180	0.9045
No log	1.0323	32	0.6053	-0.0081	0.6053	0.7780
No log	1.0968	34	0.6100	0.0	0.6100	0.7810
No log	1.1613	36	0.6821	-0.0496	0.6821	0.8259
No log	1.2258	38	0.8609	0.0569	0.8609	0.9279
No log	1.2903	40	0.9018	0.0345	0.9018	0.9497
No log	1.3548	42	1.1343	0.0	1.1343	1.0650
No log	1.4194	44	1.1418	0.0345	1.1418	1.0686
No log	1.4839	46	0.8547	0.1000	0.8547	0.9245
No log	1.5484	48	0.6695	0.1111	0.6695	0.8183
No log	1.6129	50	0.6635	0.0769	0.6635	0.8145
No log	1.6774	52	0.8013	0.1416	0.8013	0.8952
No log	1.7419	54	0.8412	0.0288	0.8412	0.9172
No log	1.8065	56	0.9177	0.0	0.9177	0.9579
No log	1.8710	58	0.9828	0.0	0.9828	0.9913
No log	1.9355	60	1.1924	0.0	1.1924	1.0920
No log	2.0	62	1.2349	0.0	1.2349	1.1112
No log	2.0645	64	1.6323	0.0	1.6323	1.2776
No log	2.1290	66	1.6851	0.0	1.6851	1.2981
No log	2.1935	68	1.1133	0.0	1.1133	1.0551
No log	2.2581	70	0.9013	-0.0041	0.9013	0.9494
No log	2.3226	72	0.7769	-0.2398	0.7769	0.8814
No log	2.3871	74	0.6513	-0.0853	0.6513	0.8071
No log	2.4516	76	0.6340	-0.0081	0.6340	0.7963
No log	2.5161	78	0.6841	-0.0667	0.6841	0.8271
No log	2.5806	80	0.8358	0.0685	0.8358	0.9142
No log	2.6452	82	1.2076	0.0345	1.2076	1.0989
No log	2.7097	84	1.0578	0.0118	1.0578	1.0285
No log	2.7742	86	0.7141	0.1398	0.7141	0.8450
No log	2.8387	88	0.7192	0.1186	0.7192	0.8481
No log	2.9032	90	0.7512	0.1475	0.7512	0.8667
No log	2.9677	92	0.7893	0.1475	0.7893	0.8884
No log	3.0323	94	1.0193	0.1055	1.0193	1.0096
No log	3.0968	96	0.8519	0.1549	0.8519	0.9230
No log	3.1613	98	0.6630	0.0327	0.6630	0.8142
No log	3.2258	100	0.6452	0.0400	0.6452	0.8033
No log	3.2903	102	0.6480	-0.0256	0.6480	0.8050
No log	3.3548	104	0.6809	0.0692	0.6809	0.8251
No log	3.4194	106	0.6891	0.0452	0.6891	0.8301
No log	3.4839	108	0.6888	-0.0186	0.6888	0.8299
No log	3.5484	110	0.6872	0.1059	0.6872	0.8290
No log	3.6129	112	0.8390	0.1765	0.8390	0.9160
No log	3.6774	114	0.7219	0.2090	0.7219	0.8497
No log	3.7419	116	0.6526	0.1220	0.6526	0.8078
No log	3.8065	118	0.6442	0.2644	0.6442	0.8026
No log	3.8710	120	0.5783	0.0452	0.5783	0.7605
No log	3.9355	122	0.6157	0.2857	0.6157	0.7847
No log	4.0	124	0.8402	0.0901	0.8402	0.9166
No log	4.0645	126	0.8798	0.1290	0.8798	0.9380
No log	4.1290	128	0.8494	0.1290	0.8494	0.9216
No log	4.1935	130	0.6838	0.2410	0.6838	0.8269
No log	4.2581	132	0.6011	0.3797	0.6011	0.7753
No log	4.3226	134	0.6140	0.3684	0.6140	0.7836
No log	4.3871	136	0.8274	0.136	0.8274	0.9096
No log	4.4516	138	1.0718	0.1524	1.0718	1.0353
No log	4.5161	140	1.1437	0.0976	1.1437	1.0694
No log	4.5806	142	1.1475	0.1186	1.1475	1.0712
No log	4.6452	144	0.9184	0.1276	0.9184	0.9584
No log	4.7097	146	0.6951	0.3208	0.6951	0.8337
No log	4.7742	148	0.6701	0.3180	0.6701	0.8186
No log	4.8387	150	0.9774	0.2000	0.9774	0.9886
No log	4.9032	152	1.0978	0.1587	1.0978	1.0477
No log	4.9677	154	1.1539	0.1304	1.1539	1.0742
No log	5.0323	156	0.9554	0.264	0.9554	0.9774
No log	5.0968	158	0.9422	0.2327	0.9422	0.9707
No log	5.1613	160	0.8870	0.1169	0.8870	0.9418
No log	5.2258	162	1.0429	0.1937	1.0429	1.0212
No log	5.2903	164	1.4029	0.0769	1.4029	1.1844
No log	5.3548	166	1.4327	0.0062	1.4327	1.1970
No log	5.4194	168	1.0836	0.1940	1.0836	1.0410
No log	5.4839	170	0.8202	0.25	0.8202	0.9057
No log	5.5484	172	0.8117	0.2566	0.8117	0.9009
No log	5.6129	174	1.0417	0.1940	1.0417	1.0206
No log	5.6774	176	1.1784	0.0933	1.1784	1.0855
No log	5.7419	178	1.0357	0.1648	1.0357	1.0177
No log	5.8065	180	0.8087	0.1644	0.8087	0.8993
No log	5.8710	182	0.8537	0.1790	0.8537	0.9239
No log	5.9355	184	0.9963	0.0958	0.9963	0.9982
No log	6.0	186	0.9509	0.1803	0.9509	0.9752
No log	6.0645	188	0.9567	0.1803	0.9567	0.9781
No log	6.1290	190	0.9851	0.1235	0.9851	0.9925
No log	6.1935	192	1.1509	0.1158	1.1509	1.0728
No log	6.2581	194	1.0757	0.1692	1.0757	1.0372
No log	6.3226	196	0.9979	0.1621	0.9979	0.9990
No log	6.3871	198	0.8892	0.2000	0.8892	0.9430
No log	6.4516	200	0.9404	0.1165	0.9404	0.9698
No log	6.5161	202	1.1303	0.2000	1.1303	1.0631
No log	6.5806	204	1.1575	0.2000	1.1575	1.0759
No log	6.6452	206	1.1567	0.2308	1.1567	1.0755
No log	6.7097	208	1.0897	0.1938	1.0897	1.0439
No log	6.7742	210	0.9888	0.2000	0.9888	0.9944
No log	6.8387	212	0.9944	0.2239	0.9944	0.9972
No log	6.9032	214	1.0592	0.2121	1.0592	1.0292
No log	6.9677	216	1.0335	0.2121	1.0335	1.0166
No log	7.0323	218	1.0991	0.1642	1.0991	1.0484
No log	7.0968	220	1.0597	0.2177	1.0597	1.0294
No log	7.1613	222	1.1030	0.1704	1.1030	1.0502
No log	7.2258	224	1.1688	0.1418	1.1688	1.0811
No log	7.2903	226	1.2364	0.1429	1.2364	1.1119
No log	7.3548	228	1.2063	0.1418	1.2063	1.0983
No log	7.4194	230	1.0258	0.1343	1.0258	1.0128
No log	7.4839	232	0.8979	0.2000	0.8979	0.9476
No log	7.5484	234	0.9196	0.2327	0.9196	0.9589
No log	7.6129	236	1.0718	0.1642	1.0718	1.0353
No log	7.6774	238	1.1943	0.1418	1.1943	1.0928
No log	7.7419	240	1.1943	0.1418	1.1943	1.0929
No log	7.8065	242	1.0453	0.1587	1.0453	1.0224
No log	7.8710	244	0.8891	0.2000	0.8891	0.9429
No log	7.9355	246	0.8057	0.3422	0.8057	0.8976
No log	8.0	248	0.8123	0.25	0.8123	0.9013
No log	8.0645	250	0.9019	0.2000	0.9019	0.9497
No log	8.1290	252	0.9989	0.1278	0.9989	0.9995
No log	8.1935	254	1.1117	0.2000	1.1117	1.0544
No log	8.2581	256	1.1668	0.2296	1.1668	1.0802
No log	8.3226	258	1.0990	0.1692	1.0990	1.0483
No log	8.3871	260	1.0099	0.2253	1.0099	1.0050
No log	8.4516	262	0.9571	0.2258	0.9571	0.9783
No log	8.5161	264	0.9049	0.1807	0.9049	0.9513
No log	8.5806	266	0.9488	0.2258	0.9488	0.9741
No log	8.6452	268	1.0307	0.2558	1.0307	1.0152
No log	8.7097	270	1.0933	0.2302	1.0933	1.0456
No log	8.7742	272	1.1697	0.2000	1.1697	1.0815
No log	8.8387	274	1.2207	0.2121	1.2207	1.1049
No log	8.9032	276	1.1666	0.2000	1.1666	1.0801
No log	8.9677	278	1.1044	0.2302	1.1044	1.0509
No log	9.0323	280	1.0412	0.2558	1.0412	1.0204
No log	9.0968	282	0.9695	0.2258	0.9695	0.9846
No log	9.1613	284	0.9487	0.2258	0.9487	0.9740
No log	9.2258	286	0.9713	0.2258	0.9713	0.9855
No log	9.2903	288	0.9790	0.2258	0.9790	0.9894
No log	9.3548	290	0.9997	0.2258	0.9997	0.9998
No log	9.4194	292	1.0564	0.2327	1.0564	1.0278
No log	9.4839	294	1.1143	0.2000	1.1143	1.0556
No log	9.5484	296	1.1208	0.2000	1.1208	1.0587
No log	9.6129	298	1.1036	0.2000	1.1036	1.0505
No log	9.6774	300	1.0685	0.2000	1.0685	1.0337
No log	9.7419	302	1.0312	0.2258	1.0312	1.0155
No log	9.8065	304	1.0130	0.2258	1.0130	1.0065
No log	9.8710	306	1.0113	0.2258	1.0113	1.0056
No log	9.9355	308	1.0145	0.2258	1.0145	1.0072
No log	10.0	310	1.0147	0.2258	1.0147	1.0073

Framework versions

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