ArabicNewSplits5_FineTuningAraBERT_run2_AugV5_k4_task2_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: 0.7411
• Qwk: 0.5554
• Mse: 0.7411
• Rmse: 0.8608

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	0.0714	2	3.9188	-0.0187	3.9188	1.9796
No log	0.1429	4	2.1169	0.0472	2.1169	1.4550
No log	0.2143	6	1.2679	0.0127	1.2679	1.1260
No log	0.2857	8	2.1597	-0.0938	2.1597	1.4696
No log	0.3571	10	2.4915	-0.0614	2.4915	1.5784
No log	0.4286	12	1.4161	0.0550	1.4161	1.1900
No log	0.5	14	0.7151	0.2577	0.7151	0.8456
No log	0.5714	16	0.6714	0.2378	0.6714	0.8194
No log	0.6429	18	0.6701	0.3030	0.6701	0.8186
No log	0.7143	20	0.7481	0.1220	0.7481	0.8649
No log	0.7857	22	0.9949	0.1348	0.9949	0.9974
No log	0.8571	24	1.4932	0.1646	1.4932	1.2220
No log	0.9286	26	1.8555	0.1793	1.8555	1.3622
No log	1.0	28	1.4970	0.1794	1.4970	1.2235
No log	1.0714	30	1.2308	0.1395	1.2308	1.1094
No log	1.1429	32	1.1070	0.1629	1.1070	1.0521
No log	1.2143	34	0.9928	0.1731	0.9928	0.9964
No log	1.2857	36	0.8917	0.1353	0.8917	0.9443
No log	1.3571	38	0.7834	0.1912	0.7834	0.8851
No log	1.4286	40	0.6632	0.3633	0.6632	0.8144
No log	1.5	42	0.5945	0.4092	0.5945	0.7711
No log	1.5714	44	0.6008	0.4486	0.6008	0.7751
No log	1.6429	46	0.6711	0.3784	0.6711	0.8192
No log	1.7143	48	0.7705	0.3079	0.7705	0.8778
No log	1.7857	50	0.8313	0.2874	0.8313	0.9118
No log	1.8571	52	0.9152	0.2575	0.9152	0.9567
No log	1.9286	54	1.0271	0.2491	1.0271	1.0135
No log	2.0	56	1.2482	0.2207	1.2482	1.1172
No log	2.0714	58	1.5427	0.2015	1.5427	1.2421
No log	2.1429	60	1.4863	0.2107	1.4863	1.2191
No log	2.2143	62	1.2116	0.2009	1.2116	1.1007
No log	2.2857	64	0.9190	0.2437	0.9190	0.9586
No log	2.3571	66	0.8022	0.2626	0.8022	0.8956
No log	2.4286	68	0.6805	0.4151	0.6805	0.8249
No log	2.5	70	0.6598	0.4153	0.6598	0.8123
No log	2.5714	72	0.6942	0.4512	0.6942	0.8332
No log	2.6429	74	0.7884	0.4364	0.7884	0.8879
No log	2.7143	76	0.8031	0.4745	0.8031	0.8961
No log	2.7857	78	0.6643	0.4535	0.6643	0.8151
No log	2.8571	80	0.5426	0.4550	0.5426	0.7366
No log	2.9286	82	0.5288	0.4799	0.5288	0.7272
No log	3.0	84	0.5290	0.4951	0.5290	0.7273
No log	3.0714	86	0.5487	0.5	0.5487	0.7408
No log	3.1429	88	0.5391	0.4960	0.5391	0.7343
No log	3.2143	90	0.5660	0.4719	0.5660	0.7523
No log	3.2857	92	0.6174	0.5044	0.6174	0.7857
No log	3.3571	94	0.5637	0.5020	0.5637	0.7508
No log	3.4286	96	0.5535	0.5128	0.5535	0.7439
No log	3.5	98	0.5894	0.4790	0.5894	0.7677
No log	3.5714	100	0.5558	0.4843	0.5558	0.7455
No log	3.6429	102	0.5467	0.4996	0.5467	0.7394
No log	3.7143	104	0.5392	0.4968	0.5392	0.7343
No log	3.7857	106	0.5850	0.4924	0.5850	0.7648
No log	3.8571	108	0.6763	0.4889	0.6763	0.8224
No log	3.9286	110	0.7235	0.5290	0.7235	0.8506
No log	4.0	112	0.8295	0.4977	0.8295	0.9108
No log	4.0714	114	0.7837	0.5419	0.7837	0.8853
No log	4.1429	116	0.6240	0.5543	0.6240	0.7899
No log	4.2143	118	0.5980	0.5790	0.5980	0.7733
No log	4.2857	120	0.5774	0.5366	0.5774	0.7598
No log	4.3571	122	0.5599	0.5074	0.5599	0.7483
No log	4.4286	124	0.5918	0.5812	0.5918	0.7693
No log	4.5	126	0.6007	0.5403	0.6007	0.7751
No log	4.5714	128	0.5892	0.5486	0.5892	0.7676
No log	4.6429	130	0.6036	0.5222	0.6036	0.7769
No log	4.7143	132	0.6457	0.5208	0.6457	0.8036
No log	4.7857	134	0.6454	0.5047	0.6454	0.8033
No log	4.8571	136	0.6422	0.5231	0.6422	0.8014
No log	4.9286	138	0.6452	0.5226	0.6452	0.8033
No log	5.0	140	0.6520	0.5728	0.6520	0.8075
No log	5.0714	142	0.6695	0.5731	0.6695	0.8182
No log	5.1429	144	0.6947	0.5566	0.6947	0.8335
No log	5.2143	146	0.7096	0.5907	0.7096	0.8424
No log	5.2857	148	0.7095	0.5911	0.7095	0.8423
No log	5.3571	150	0.7038	0.5871	0.7038	0.8390
No log	5.4286	152	0.6960	0.5593	0.6960	0.8343
No log	5.5	154	0.6723	0.5984	0.6723	0.8199
No log	5.5714	156	0.6629	0.5983	0.6629	0.8142
No log	5.6429	158	0.6607	0.5686	0.6607	0.8128
No log	5.7143	160	0.6623	0.5702	0.6623	0.8138
No log	5.7857	162	0.6759	0.5438	0.6759	0.8221
No log	5.8571	164	0.6809	0.5634	0.6809	0.8251
No log	5.9286	166	0.7008	0.5457	0.7008	0.8371
No log	6.0	168	0.7442	0.5155	0.7442	0.8627
No log	6.0714	170	0.7924	0.5248	0.7924	0.8902
No log	6.1429	172	0.7705	0.5093	0.7705	0.8778
No log	6.2143	174	0.7208	0.5577	0.7208	0.8490
No log	6.2857	176	0.7218	0.5752	0.7218	0.8496
No log	6.3571	178	0.7355	0.5806	0.7355	0.8576
No log	6.4286	180	0.7547	0.5671	0.7547	0.8687
No log	6.5	182	0.7774	0.5284	0.7774	0.8817
No log	6.5714	184	0.8009	0.5002	0.8009	0.8950
No log	6.6429	186	0.8187	0.5085	0.8187	0.9048
No log	6.7143	188	0.7988	0.5230	0.7988	0.8938
No log	6.7857	190	0.7787	0.5473	0.7787	0.8824
No log	6.8571	192	0.7922	0.5492	0.7922	0.8901
No log	6.9286	194	0.8019	0.5780	0.8019	0.8955
No log	7.0	196	0.7709	0.5676	0.7709	0.8780
No log	7.0714	198	0.7286	0.5826	0.7286	0.8536
No log	7.1429	200	0.7088	0.5886	0.7088	0.8419
No log	7.2143	202	0.6958	0.5843	0.6958	0.8341
No log	7.2857	204	0.6902	0.6085	0.6902	0.8308
No log	7.3571	206	0.6991	0.5620	0.6991	0.8361
No log	7.4286	208	0.7041	0.54	0.7041	0.8391
No log	7.5	210	0.6955	0.5339	0.6955	0.8340
No log	7.5714	212	0.6932	0.5554	0.6932	0.8326
No log	7.6429	214	0.7044	0.5450	0.7044	0.8393
No log	7.7143	216	0.7032	0.5848	0.7032	0.8386
No log	7.7857	218	0.7042	0.5901	0.7042	0.8392
No log	7.8571	220	0.6919	0.5899	0.6919	0.8318
No log	7.9286	222	0.6884	0.5958	0.6884	0.8297
No log	8.0	224	0.6899	0.5958	0.6899	0.8306
No log	8.0714	226	0.6875	0.5953	0.6875	0.8292
No log	8.1429	228	0.6888	0.5792	0.6888	0.8299
No log	8.2143	230	0.6886	0.5825	0.6886	0.8298
No log	8.2857	232	0.6901	0.5825	0.6901	0.8308
No log	8.3571	234	0.6935	0.5808	0.6935	0.8328
No log	8.4286	236	0.7080	0.5805	0.7080	0.8414
No log	8.5	238	0.7229	0.5752	0.7229	0.8502
No log	8.5714	240	0.7279	0.5789	0.7279	0.8532
No log	8.6429	242	0.7333	0.5851	0.7333	0.8564
No log	8.7143	244	0.7443	0.6015	0.7443	0.8627
No log	8.7857	246	0.7507	0.5943	0.7507	0.8664
No log	8.8571	248	0.7583	0.5845	0.7583	0.8708
No log	8.9286	250	0.7620	0.5862	0.7620	0.8730
No log	9.0	252	0.7621	0.6060	0.7621	0.8730
No log	9.0714	254	0.7604	0.6060	0.7604	0.8720
No log	9.1429	256	0.7577	0.6078	0.7577	0.8705
No log	9.2143	258	0.7598	0.5755	0.7598	0.8716
No log	9.2857	260	0.7605	0.5592	0.7605	0.8721
No log	9.3571	262	0.7565	0.5592	0.7565	0.8698
No log	9.4286	264	0.7550	0.5592	0.7550	0.8689
No log	9.5	266	0.7541	0.5555	0.7541	0.8684
No log	9.5714	268	0.7521	0.5554	0.7521	0.8672
No log	9.6429	270	0.7509	0.5504	0.7509	0.8666
No log	9.7143	272	0.7473	0.5554	0.7473	0.8644
No log	9.7857	274	0.7430	0.5554	0.7430	0.8620
No log	9.8571	276	0.7411	0.5554	0.7411	0.8609
No log	9.9286	278	0.7411	0.5554	0.7411	0.8609
No log	10.0	280	0.7411	0.5554	0.7411	0.8608

Framework versions

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