ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k4_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: 0.8806
• Qwk: 0.2450
• Mse: 0.8806
• Rmse: 0.9384

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	0.0769	2	3.3177	-0.0138	3.3177	1.8215
No log	0.1538	4	1.7343	-0.0070	1.7343	1.3169
No log	0.2308	6	1.3229	0.0255	1.3229	1.1502
No log	0.3077	8	0.8686	0.0270	0.8686	0.9320
No log	0.3846	10	0.8810	0.1456	0.8810	0.9386
No log	0.4615	12	0.8243	0.1913	0.8243	0.9079
No log	0.5385	14	0.9622	0.1238	0.9622	0.9809
No log	0.6154	16	1.6814	0.0751	1.6814	1.2967
No log	0.6923	18	1.6105	0.0464	1.6105	1.2691
No log	0.7692	20	1.1546	0.0078	1.1546	1.0745
No log	0.8462	22	0.6405	0.2418	0.6405	0.8003
No log	0.9231	24	0.5796	0.0	0.5796	0.7613
No log	1.0	26	0.5863	0.0	0.5863	0.7657
No log	1.0769	28	0.6176	0.0	0.6176	0.7859
No log	1.1538	30	0.7344	0.2077	0.7344	0.8570
No log	1.2308	32	0.7264	0.1919	0.7264	0.8523
No log	1.3077	34	0.9274	0.1333	0.9274	0.9630
No log	1.3846	36	1.0097	0.1055	1.0097	1.0049
No log	1.4615	38	0.7296	0.1264	0.7296	0.8542
No log	1.5385	40	0.7506	0.0952	0.7506	0.8664
No log	1.6154	42	1.0098	0.1570	1.0098	1.0049
No log	1.6923	44	0.8213	0.0734	0.8213	0.9063
No log	1.7692	46	0.7557	0.0952	0.7557	0.8693
No log	1.8462	48	0.6425	-0.0068	0.6425	0.8015
No log	1.9231	50	0.6396	0.0	0.6396	0.7997
No log	2.0	52	0.6393	0.0	0.6393	0.7996
No log	2.0769	54	0.7133	0.1429	0.7133	0.8446
No log	2.1538	56	0.5729	0.0556	0.5729	0.7569
No log	2.2308	58	0.5995	0.1605	0.5995	0.7743
No log	2.3077	60	0.8285	0.2356	0.8285	0.9102
No log	2.3846	62	0.7799	0.1852	0.7799	0.8831
No log	2.4615	64	0.5928	0.2090	0.5928	0.7699
No log	2.5385	66	0.6439	0.2174	0.6439	0.8024
No log	2.6154	68	0.8237	0.0909	0.8237	0.9076
No log	2.6923	70	0.6442	0.3498	0.6442	0.8026
No log	2.7692	72	0.6555	0.1691	0.6555	0.8096
No log	2.8462	74	0.6749	0.2150	0.6749	0.8215
No log	2.9231	76	0.8681	0.1803	0.8681	0.9317
No log	3.0	78	1.2276	-0.0769	1.2276	1.1080
No log	3.0769	80	1.1750	-0.1429	1.1750	1.0840
No log	3.1538	82	1.0351	-0.0420	1.0351	1.0174
No log	3.2308	84	0.8206	0.1730	0.8206	0.9059
No log	3.3077	86	0.8287	0.2066	0.8287	0.9103
No log	3.3846	88	1.0769	0.1329	1.0769	1.0377
No log	3.4615	90	1.2830	0.0710	1.2830	1.1327
No log	3.5385	92	1.0680	0.1329	1.0680	1.0334
No log	3.6154	94	0.8081	0.3000	0.8081	0.8989
No log	3.6923	96	0.6762	0.3939	0.6762	0.8223
No log	3.7692	98	0.6624	0.3143	0.6624	0.8139
No log	3.8462	100	0.8199	0.2618	0.8199	0.9055
No log	3.9231	102	1.4582	0.1447	1.4582	1.2076
No log	4.0	104	1.5582	0.1447	1.5582	1.2483
No log	4.0769	106	1.1438	0.1769	1.1438	1.0695
No log	4.1538	108	1.1151	0.2360	1.1151	1.0560
No log	4.2308	110	1.2775	0.1032	1.2775	1.1303
No log	4.3077	112	1.1965	0.1541	1.1965	1.0938
No log	4.3846	114	1.2696	0.1329	1.2696	1.1267
No log	4.4615	116	1.0018	0.2481	1.0018	1.0009
No log	4.5385	118	0.7437	0.3518	0.7437	0.8624
No log	4.6154	120	0.7530	0.3518	0.7530	0.8678
No log	4.6923	122	0.9239	0.2441	0.9239	0.9612
No log	4.7692	124	1.5229	0.1220	1.5229	1.2341
No log	4.8462	126	1.6386	0.0145	1.6386	1.2801
No log	4.9231	128	1.4856	0.1220	1.4856	1.2188
No log	5.0	130	1.0480	0.1880	1.0480	1.0237
No log	5.0769	132	0.6839	0.3394	0.6839	0.8270
No log	5.1538	134	0.6479	0.3427	0.6479	0.8049
No log	5.2308	136	0.7509	0.3305	0.7509	0.8666
No log	5.3077	138	0.9557	0.1318	0.9557	0.9776
No log	5.3846	140	1.1646	0.1429	1.1646	1.0791
No log	5.4615	142	1.1776	0.1238	1.1776	1.0852
No log	5.5385	144	0.9385	0.1378	0.9385	0.9688
No log	5.6154	146	0.5945	0.3786	0.5945	0.7711
No log	5.6923	148	0.5941	0.3077	0.5941	0.7708
No log	5.7692	150	0.5854	0.2727	0.5854	0.7651
No log	5.8462	152	0.6955	0.4087	0.6955	0.8340
No log	5.9231	154	0.8588	0.2647	0.8588	0.9267
No log	6.0	156	1.0686	0.1141	1.0686	1.0338
No log	6.0769	158	1.1010	0.1399	1.1010	1.0493
No log	6.1538	160	0.8906	0.2593	0.8906	0.9437
No log	6.2308	162	0.6764	0.3391	0.6764	0.8224
No log	6.3077	164	0.6922	0.2140	0.6922	0.8320
No log	6.3846	166	0.6929	0.1429	0.6929	0.8324
No log	6.4615	168	0.6507	0.3161	0.6507	0.8067
No log	6.5385	170	0.7492	0.2982	0.7492	0.8656
No log	6.6154	172	0.9186	0.1811	0.9186	0.9584
No log	6.6923	174	1.0594	0.1343	1.0594	1.0293
No log	6.7692	176	1.0568	0.1331	1.0568	1.0280
No log	6.8462	178	0.8996	0.1807	0.8996	0.9485
No log	6.9231	180	0.7184	0.3744	0.7184	0.8476
No log	7.0	182	0.6949	0.0857	0.6949	0.8336
No log	7.0769	184	0.7564	0.2000	0.7564	0.8697
No log	7.1538	186	0.7182	0.1220	0.7182	0.8474
No log	7.2308	188	0.6869	0.3365	0.6869	0.8288
No log	7.3077	190	0.8453	0.2414	0.8453	0.9194
No log	7.3846	192	1.1290	0.0746	1.1290	1.0625
No log	7.4615	194	1.2068	0.0833	1.2068	1.0986
No log	7.5385	196	1.1054	0.0769	1.1054	1.0514
No log	7.6154	198	0.9334	0.1807	0.9334	0.9661
No log	7.6923	200	0.8424	0.2340	0.8424	0.9178
No log	7.7692	202	0.7860	0.3116	0.7860	0.8866
No log	7.8462	204	0.7714	0.3028	0.7714	0.8783
No log	7.9231	206	0.7620	0.3028	0.7620	0.8730
No log	8.0	208	0.8424	0.2340	0.8424	0.9178
No log	8.0769	210	1.0015	0.1562	1.0015	1.0008
No log	8.1538	212	1.0890	0.1014	1.0890	1.0435
No log	8.2308	214	1.0975	0.1014	1.0975	1.0476
No log	8.3077	216	0.9972	0.1562	0.9972	0.9986
No log	8.3846	218	0.9698	0.1562	0.9698	0.9848
No log	8.4615	220	0.9070	0.264	0.9070	0.9524
No log	8.5385	222	0.8062	0.2593	0.8062	0.8979
No log	8.6154	224	0.7274	0.4074	0.7274	0.8529
No log	8.6923	226	0.7096	0.4074	0.7096	0.8424
No log	8.7692	228	0.7217	0.4074	0.7217	0.8495
No log	8.8462	230	0.7442	0.3363	0.7442	0.8627
No log	8.9231	232	0.7663	0.3333	0.7663	0.8754
No log	9.0	234	0.7925	0.2333	0.7925	0.8902
No log	9.0769	236	0.8001	0.2479	0.8001	0.8945
No log	9.1538	238	0.8170	0.2131	0.8170	0.9039
No log	9.2308	240	0.8204	0.2131	0.8204	0.9057
No log	9.3077	242	0.8476	0.2131	0.8476	0.9207
No log	9.3846	244	0.8535	0.2131	0.8535	0.9239
No log	9.4615	246	0.8654	0.2131	0.8654	0.9302
No log	9.5385	248	0.8806	0.1870	0.8806	0.9384
No log	9.6154	250	0.8871	0.1870	0.8871	0.9418
No log	9.6923	252	0.8964	0.1870	0.8964	0.9468
No log	9.7692	254	0.8931	0.1870	0.8931	0.9450
No log	9.8462	256	0.8927	0.1870	0.8927	0.9449
No log	9.9231	258	0.8858	0.1870	0.8858	0.9412
No log	10.0	260	0.8806	0.2450	0.8806	0.9384

Framework versions

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