ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k6_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: 0.6050
• Qwk: 0.3161
• Mse: 0.6050
• Rmse: 0.7778

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	0.0667	2	3.0885	-0.0114	3.0885	1.7574
No log	0.1333	4	1.5351	-0.0070	1.5351	1.2390
No log	0.2	6	0.9492	0.0462	0.9492	0.9743
No log	0.2667	8	0.7810	0.1770	0.7810	0.8837
No log	0.3333	10	0.6009	0.0569	0.6009	0.7752
No log	0.4	12	0.6257	-0.0732	0.6257	0.7910
No log	0.4667	14	0.6285	-0.0732	0.6285	0.7928
No log	0.5333	16	0.6139	0.1008	0.6139	0.7835
No log	0.6	18	0.8207	0.1276	0.8207	0.9059
No log	0.6667	20	0.8019	0.2000	0.8019	0.8955
No log	0.7333	22	0.9251	0.0476	0.9251	0.9618
No log	0.8	24	0.6633	0.1638	0.6633	0.8144
No log	0.8667	26	0.6217	0.0725	0.6217	0.7885
No log	0.9333	28	0.6255	0.1895	0.6255	0.7909
No log	1.0	30	0.6375	0.2201	0.6375	0.7985
No log	1.0667	32	0.5666	0.1008	0.5666	0.7528
No log	1.1333	34	0.5833	0.0815	0.5833	0.7637
No log	1.2	36	0.6911	0.2184	0.6911	0.8314
No log	1.2667	38	0.6013	0.0556	0.6013	0.7754
No log	1.3333	40	0.5894	0.0556	0.5894	0.7677
No log	1.4	42	0.6202	0.1020	0.6202	0.7875
No log	1.4667	44	0.6079	0.0556	0.6079	0.7797
No log	1.5333	46	0.5657	0.1008	0.5657	0.7521
No log	1.6	48	0.5624	0.0476	0.5624	0.7500
No log	1.6667	50	0.5382	0.1008	0.5382	0.7336
No log	1.7333	52	0.5505	0.1407	0.5505	0.7420
No log	1.8	54	0.5360	0.1515	0.5360	0.7321
No log	1.8667	56	0.5506	0.1429	0.5506	0.7420
No log	1.9333	58	0.5845	0.1448	0.5845	0.7645
No log	2.0	60	0.6109	0.0526	0.6109	0.7816
No log	2.0667	62	0.6247	0.1529	0.6247	0.7904
No log	2.1333	64	0.5811	0.1895	0.5811	0.7623
No log	2.2	66	0.6946	0.3023	0.6946	0.8334
No log	2.2667	68	0.7021	0.2626	0.7021	0.8379
No log	2.3333	70	0.6732	0.2189	0.6732	0.8205
No log	2.4	72	0.5593	0.4091	0.5593	0.7478
No log	2.4667	74	0.5674	0.2941	0.5674	0.7533
No log	2.5333	76	0.6960	0.3402	0.6960	0.8343
No log	2.6	78	0.8435	0.1870	0.8435	0.9184
No log	2.6667	80	1.1961	0.1693	1.1961	1.0937
No log	2.7333	82	0.8071	0.2208	0.8071	0.8984
No log	2.8	84	0.6381	0.2157	0.6381	0.7988
No log	2.8667	86	0.8381	0.2681	0.8381	0.9155
No log	2.9333	88	0.6315	0.2222	0.6315	0.7947
No log	3.0	90	0.8999	0.1486	0.8999	0.9486
No log	3.0667	92	1.2449	0.1389	1.2449	1.1157
No log	3.1333	94	1.0013	0.0677	1.0013	1.0007
No log	3.2	96	0.8263	0.2000	0.8263	0.9090
No log	3.2667	98	0.9594	0.0427	0.9594	0.9795
No log	3.3333	100	1.4039	0.0891	1.4039	1.1848
No log	3.4	102	1.5565	0.0732	1.5565	1.2476
No log	3.4667	104	1.2232	0.1367	1.2232	1.1060
No log	3.5333	106	0.7894	0.3043	0.7894	0.8885
No log	3.6	108	0.8273	0.3496	0.8273	0.9096
No log	3.6667	110	1.1843	0.1304	1.1843	1.0882
No log	3.7333	112	1.2679	0.0872	1.2679	1.1260
No log	3.8	114	1.5132	0.0943	1.5132	1.2301
No log	3.8667	116	1.3942	0.1111	1.3942	1.1808
No log	3.9333	118	1.0093	0.1655	1.0093	1.0046
No log	4.0	120	0.9533	0.1939	0.9533	0.9763
No log	4.0667	122	0.8747	0.2581	0.8747	0.9352
No log	4.1333	124	0.7696	0.2661	0.7696	0.8773
No log	4.2	126	0.8337	0.2432	0.8337	0.9130
No log	4.2667	128	0.7974	0.2607	0.7974	0.8930
No log	4.3333	130	0.7150	0.2637	0.7150	0.8456
No log	4.4	132	0.6350	0.3478	0.6350	0.7968
No log	4.4667	134	0.6937	0.2965	0.6937	0.8329
No log	4.5333	136	0.8855	0.1148	0.8855	0.9410
No log	4.6	138	0.8278	0.1416	0.8278	0.9098
No log	4.6667	140	0.6691	0.3131	0.6691	0.8180
No log	4.7333	142	0.6777	0.3103	0.6777	0.8232
No log	4.8	144	0.7845	0.2150	0.7845	0.8857
No log	4.8667	146	0.9391	0.1579	0.9391	0.9691
No log	4.9333	148	1.0481	0.1601	1.0481	1.0238
No log	5.0	150	0.8745	0.1235	0.8745	0.9351
No log	5.0667	152	0.6263	0.3231	0.6263	0.7914
No log	5.1333	154	0.6145	0.3939	0.6145	0.7839
No log	5.2	156	0.7633	0.2143	0.7633	0.8737
No log	5.2667	158	0.9994	0.1882	0.9994	0.9997
No log	5.3333	160	0.8366	0.2140	0.8366	0.9147
No log	5.4	162	0.6509	0.3535	0.6509	0.8068
No log	5.4667	164	0.6577	0.3433	0.6577	0.8110
No log	5.5333	166	0.7429	0.2762	0.7429	0.8619
No log	5.6	168	0.9928	0.0598	0.9928	0.9964
No log	5.6667	170	1.0396	0.0958	1.0396	1.0196
No log	5.7333	172	0.8052	0.2536	0.8052	0.8973
No log	5.8	174	0.7298	0.3143	0.7298	0.8543
No log	5.8667	176	0.8009	0.2233	0.8009	0.8949
No log	5.9333	178	0.9157	0.0871	0.9157	0.9569
No log	6.0	180	0.8822	0.1504	0.8822	0.9393
No log	6.0667	182	0.8586	0.2233	0.8586	0.9266
No log	6.1333	184	0.7923	0.2000	0.7923	0.8901
No log	6.2	186	0.7860	0.2153	0.7860	0.8866
No log	6.2667	188	0.9448	0.1562	0.9448	0.9720
No log	6.3333	190	1.1101	0.1317	1.1101	1.0536
No log	6.4	192	0.9768	0.1880	0.9768	0.9883
No log	6.4667	194	0.7415	0.2881	0.7415	0.8611
No log	6.5333	196	0.6107	0.4231	0.6107	0.7815
No log	6.6	198	0.6137	0.4231	0.6137	0.7834
No log	6.6667	200	0.6944	0.3874	0.6944	0.8333
No log	6.7333	202	0.8485	0.2129	0.8485	0.9212
No log	6.8	204	0.9104	0.2184	0.9104	0.9542
No log	6.8667	206	0.7548	0.2523	0.7548	0.8688
No log	6.9333	208	0.6361	0.3103	0.6361	0.7976
No log	7.0	210	0.5726	0.4573	0.5726	0.7567
No log	7.0667	212	0.5609	0.4573	0.5609	0.7490
No log	7.1333	214	0.5975	0.3684	0.5975	0.7730
No log	7.2	216	0.7122	0.2637	0.7122	0.8439
No log	7.2667	218	0.7380	0.2637	0.7380	0.8591
No log	7.3333	220	0.6516	0.2563	0.6516	0.8072
No log	7.4	222	0.6018	0.3769	0.6018	0.7757
No log	7.4667	224	0.6003	0.3769	0.6003	0.7748
No log	7.5333	226	0.6435	0.2727	0.6435	0.8022
No log	7.6	228	0.6670	0.2780	0.6670	0.8167
No log	7.6667	230	0.6535	0.2727	0.6535	0.8084
No log	7.7333	232	0.6667	0.2709	0.6667	0.8165
No log	7.8	234	0.7118	0.2871	0.7118	0.8437
No log	7.8667	236	0.7734	0.2536	0.7734	0.8794
No log	7.9333	238	0.7652	0.2536	0.7652	0.8747
No log	8.0	240	0.7112	0.2871	0.7112	0.8433
No log	8.0667	242	0.6623	0.2917	0.6623	0.8138
No log	8.1333	244	0.6557	0.2917	0.6557	0.8097
No log	8.2	246	0.6510	0.3016	0.6510	0.8069
No log	8.2667	248	0.6327	0.3016	0.6327	0.7954
No log	8.3333	250	0.6653	0.3016	0.6653	0.8157
No log	8.4	252	0.6734	0.3016	0.6734	0.8206
No log	8.4667	254	0.7075	0.2941	0.7075	0.8411
No log	8.5333	256	0.7821	0.2897	0.7821	0.8844
No log	8.6	258	0.8005	0.2897	0.8005	0.8947
No log	8.6667	260	0.7820	0.2897	0.7820	0.8843
No log	8.7333	262	0.7233	0.28	0.7233	0.8505
No log	8.8	264	0.6689	0.2821	0.6689	0.8178
No log	8.8667	266	0.6627	0.3131	0.6627	0.8141
No log	8.9333	268	0.6664	0.3131	0.6664	0.8163
No log	9.0	270	0.7020	0.2821	0.7020	0.8378
No log	9.0667	272	0.7166	0.28	0.7166	0.8465
No log	9.1333	274	0.7172	0.28	0.7172	0.8469
No log	9.2	276	0.7136	0.28	0.7136	0.8447
No log	9.2667	278	0.7277	0.2780	0.7277	0.8531
No log	9.3333	280	0.7083	0.28	0.7083	0.8416
No log	9.4	282	0.6790	0.3131	0.6790	0.8240
No log	9.4667	284	0.6606	0.3131	0.6606	0.8128
No log	9.5333	286	0.6495	0.3131	0.6495	0.8059
No log	9.6	288	0.6336	0.3131	0.6336	0.7960
No log	9.6667	290	0.6188	0.3131	0.6188	0.7866
No log	9.7333	292	0.6105	0.3161	0.6105	0.7814
No log	9.8	294	0.6048	0.3161	0.6048	0.7777
No log	9.8667	296	0.6026	0.3191	0.6026	0.7763
No log	9.9333	298	0.6037	0.3191	0.6037	0.7770
No log	10.0	300	0.6050	0.3161	0.6050	0.7778

Framework versions

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