ArabicNewSplits6_FineTuningAraBERT_run2_AugV5_k5_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: 0.7760
• Qwk: 0.5298
• Mse: 0.7760
• Rmse: 0.8809

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	4.0468	-0.0150	4.0468	2.0117
No log	0.1538	4	1.9673	0.0735	1.9673	1.4026
No log	0.2308	6	1.1043	0.0313	1.1043	1.0509
No log	0.3077	8	1.1644	0.0047	1.1644	1.0791
No log	0.3846	10	0.7832	0.1716	0.7832	0.8850
No log	0.4615	12	0.7175	0.1698	0.7175	0.8471
No log	0.5385	14	0.7318	0.2980	0.7318	0.8555
No log	0.6154	16	0.7203	0.2994	0.7203	0.8487
No log	0.6923	18	0.6735	0.2942	0.6735	0.8206
No log	0.7692	20	0.6582	0.2015	0.6582	0.8113
No log	0.8462	22	0.6463	0.3530	0.6463	0.8039
No log	0.9231	24	0.6693	0.3247	0.6693	0.8181
No log	1.0	26	0.7504	0.2550	0.7504	0.8662
No log	1.0769	28	0.6955	0.3224	0.6955	0.8340
No log	1.1538	30	0.6652	0.3550	0.6652	0.8156
No log	1.2308	32	0.6133	0.3893	0.6133	0.7832
No log	1.3077	34	0.6075	0.3565	0.6075	0.7794
No log	1.3846	36	0.6635	0.3776	0.6635	0.8146
No log	1.4615	38	0.8397	0.3584	0.8397	0.9163
No log	1.5385	40	0.8144	0.3835	0.8144	0.9024
No log	1.6154	42	0.8090	0.3835	0.8090	0.8994
No log	1.6923	44	0.7603	0.3743	0.7603	0.8720
No log	1.7692	46	0.6699	0.3595	0.6699	0.8185
No log	1.8462	48	0.6400	0.3872	0.6400	0.8000
No log	1.9231	50	0.5686	0.4163	0.5686	0.7541
No log	2.0	52	0.6102	0.3802	0.6102	0.7812
No log	2.0769	54	0.6877	0.3626	0.6877	0.8293
No log	2.1538	56	0.7208	0.3337	0.7208	0.8490
No log	2.2308	58	0.6925	0.3947	0.6925	0.8322
No log	2.3077	60	0.8271	0.3263	0.8271	0.9094
No log	2.3846	62	0.7164	0.3900	0.7164	0.8464
No log	2.4615	64	0.6396	0.356	0.6396	0.7997
No log	2.5385	66	0.5471	0.5320	0.5471	0.7397
No log	2.6154	68	0.6403	0.4826	0.6403	0.8002
No log	2.6923	70	0.8450	0.3964	0.8450	0.9192
No log	2.7692	72	0.7674	0.4414	0.7674	0.8760
No log	2.8462	74	0.5958	0.5461	0.5958	0.7719
No log	2.9231	76	0.6987	0.4797	0.6987	0.8359
No log	3.0	78	0.7725	0.4503	0.7725	0.8789
No log	3.0769	80	0.6351	0.4861	0.6351	0.7969
No log	3.1538	82	0.6349	0.5335	0.6349	0.7968
No log	3.2308	84	0.6300	0.5486	0.6300	0.7937
No log	3.3077	86	0.6515	0.4642	0.6515	0.8072
No log	3.3846	88	0.7809	0.4511	0.7809	0.8837
No log	3.4615	90	1.1240	0.4168	1.1240	1.0602
No log	3.5385	92	1.0839	0.4256	1.0839	1.0411
No log	3.6154	94	0.7863	0.4644	0.7863	0.8867
No log	3.6923	96	0.6690	0.4689	0.6690	0.8179
No log	3.7692	98	0.6056	0.5167	0.6056	0.7782
No log	3.8462	100	0.6076	0.5379	0.6076	0.7795
No log	3.9231	102	0.6086	0.5364	0.6086	0.7801
No log	4.0	104	0.5779	0.5501	0.5779	0.7602
No log	4.0769	106	0.5796	0.5124	0.5796	0.7613
No log	4.1538	108	0.5855	0.5454	0.5855	0.7652
No log	4.2308	110	0.6004	0.5566	0.6004	0.7748
No log	4.3077	112	0.6361	0.5561	0.6361	0.7976
No log	4.3846	114	0.6371	0.5522	0.6371	0.7982
No log	4.4615	116	0.7530	0.5329	0.7530	0.8677
No log	4.5385	118	0.8547	0.5238	0.8547	0.9245
No log	4.6154	120	0.7596	0.5309	0.7596	0.8716
No log	4.6923	122	0.6670	0.5087	0.6670	0.8167
No log	4.7692	124	0.6007	0.5208	0.6007	0.7750
No log	4.8462	126	0.6092	0.5016	0.6092	0.7805
No log	4.9231	128	0.6236	0.5294	0.6236	0.7897
No log	5.0	130	0.6189	0.4943	0.6189	0.7867
No log	5.0769	132	0.6668	0.4868	0.6668	0.8166
No log	5.1538	134	0.6671	0.4760	0.6671	0.8167
No log	5.2308	136	0.6472	0.5217	0.6472	0.8045
No log	5.3077	138	0.6912	0.5257	0.6912	0.8314
No log	5.3846	140	0.7035	0.5257	0.7035	0.8388
No log	5.4615	142	0.6866	0.5287	0.6866	0.8286
No log	5.5385	144	0.7479	0.5270	0.7479	0.8648
No log	5.6154	146	0.7744	0.5407	0.7744	0.8800
No log	5.6923	148	0.7281	0.5413	0.7281	0.8533
No log	5.7692	150	0.6987	0.5328	0.6987	0.8359
No log	5.8462	152	0.7105	0.5358	0.7105	0.8429
No log	5.9231	154	0.7201	0.5273	0.7201	0.8486
No log	6.0	156	0.7342	0.5246	0.7342	0.8568
No log	6.0769	158	0.7556	0.5225	0.7556	0.8692
No log	6.1538	160	0.7308	0.5154	0.7308	0.8549
No log	6.2308	162	0.7072	0.5070	0.7072	0.8409
No log	6.3077	164	0.7340	0.5143	0.7340	0.8567
No log	6.3846	166	0.7601	0.5132	0.7601	0.8718
No log	6.4615	168	0.7494	0.5162	0.7494	0.8657
No log	6.5385	170	0.7298	0.5037	0.7298	0.8543
No log	6.6154	172	0.7351	0.5222	0.7351	0.8574
No log	6.6923	174	0.7475	0.5298	0.7475	0.8646
No log	6.7692	176	0.7312	0.5374	0.7312	0.8551
No log	6.8462	178	0.7376	0.5186	0.7376	0.8589
No log	6.9231	180	0.7940	0.4908	0.7940	0.8911
No log	7.0	182	0.8034	0.4978	0.8034	0.8963
No log	7.0769	184	0.7621	0.4893	0.7621	0.8730
No log	7.1538	186	0.7400	0.5296	0.7400	0.8602
No log	7.2308	188	0.7393	0.5296	0.7393	0.8598
No log	7.3077	190	0.7422	0.5133	0.7422	0.8615
No log	7.3846	192	0.7534	0.4923	0.7534	0.8680
No log	7.4615	194	0.7549	0.5045	0.7549	0.8688
No log	7.5385	196	0.7506	0.5054	0.7506	0.8664
No log	7.6154	198	0.7421	0.5054	0.7421	0.8615
No log	7.6923	200	0.7491	0.5062	0.7491	0.8655
No log	7.7692	202	0.7461	0.5062	0.7461	0.8638
No log	7.8462	204	0.7601	0.5031	0.7601	0.8718
No log	7.9231	206	0.7642	0.5031	0.7642	0.8742
No log	8.0	208	0.7505	0.5031	0.7505	0.8663
No log	8.0769	210	0.7370	0.5031	0.7370	0.8585
No log	8.1538	212	0.7280	0.5523	0.7280	0.8532
No log	8.2308	214	0.7294	0.5363	0.7294	0.8540
No log	8.3077	216	0.7322	0.5363	0.7322	0.8557
No log	8.3846	218	0.7355	0.5363	0.7355	0.8576
No log	8.4615	220	0.7344	0.5290	0.7344	0.8570
No log	8.5385	222	0.7420	0.5059	0.7420	0.8614
No log	8.6154	224	0.7562	0.5235	0.7562	0.8696
No log	8.6923	226	0.7649	0.5235	0.7649	0.8746
No log	8.7692	228	0.7707	0.5019	0.7707	0.8779
No log	8.8462	230	0.7767	0.5028	0.7767	0.8813
No log	8.9231	232	0.7821	0.5161	0.7821	0.8844
No log	9.0	234	0.7855	0.5183	0.7855	0.8863
No log	9.0769	236	0.7897	0.5183	0.7897	0.8886
No log	9.1538	238	0.7950	0.5066	0.7950	0.8916
No log	9.2308	240	0.8022	0.5029	0.8022	0.8956
No log	9.3077	242	0.8000	0.5029	0.8000	0.8944
No log	9.3846	244	0.7901	0.4960	0.7901	0.8889
No log	9.4615	246	0.7809	0.5177	0.7809	0.8837
No log	9.5385	248	0.7767	0.5298	0.7767	0.8813
No log	9.6154	250	0.7768	0.5298	0.7768	0.8814
No log	9.6923	252	0.7763	0.5298	0.7763	0.8811
No log	9.7692	254	0.7746	0.5298	0.7746	0.8801
No log	9.8462	256	0.7753	0.5298	0.7753	0.8805
No log	9.9231	258	0.7758	0.5298	0.7758	0.8808
No log	10.0	260	0.7760	0.5298	0.7760	0.8809

Framework versions

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