ArabicNewSplits6_FineTuningAraBERT_run1_AugV5_k5_task1_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: 0.6395
• Qwk: 0.7073
• Mse: 0.6395
• Rmse: 0.7997

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	0.0741	2	5.1721	-0.0024	5.1721	2.2742
No log	0.1481	4	3.2809	0.0563	3.2809	1.8113
No log	0.2222	6	2.0533	0.0478	2.0533	1.4329
No log	0.2963	8	1.4756	0.1020	1.4756	1.2148
No log	0.3704	10	1.1206	0.3739	1.1206	1.0586
No log	0.4444	12	1.0564	0.3747	1.0564	1.0278
No log	0.5185	14	0.9962	0.4436	0.9962	0.9981
No log	0.5926	16	0.8636	0.4781	0.8636	0.9293
No log	0.6667	18	0.9855	0.5060	0.9855	0.9927
No log	0.7407	20	1.0342	0.5353	1.0342	1.0170
No log	0.8148	22	1.0036	0.5403	1.0036	1.0018
No log	0.8889	24	1.1215	0.5081	1.1215	1.0590
No log	0.9630	26	1.1742	0.4853	1.1742	1.0836
No log	1.0370	28	1.6941	0.4119	1.6941	1.3016
No log	1.1111	30	1.5634	0.4291	1.5634	1.2504
No log	1.1852	32	1.1275	0.5700	1.1275	1.0619
No log	1.2593	34	0.8768	0.6513	0.8768	0.9364
No log	1.3333	36	0.8174	0.6615	0.8174	0.9041
No log	1.4074	38	0.8266	0.6596	0.8266	0.9092
No log	1.4815	40	0.8903	0.6521	0.8903	0.9436
No log	1.5556	42	1.2075	0.5348	1.2075	1.0988
No log	1.6296	44	1.1887	0.5307	1.1887	1.0903
No log	1.7037	46	0.9512	0.5868	0.9512	0.9753
No log	1.7778	48	0.6951	0.6538	0.6951	0.8337
No log	1.8519	50	0.5994	0.7398	0.5994	0.7742
No log	1.9259	52	0.6510	0.7050	0.6510	0.8068
No log	2.0	54	0.5945	0.7306	0.5945	0.7711
No log	2.0741	56	0.8334	0.6315	0.8334	0.9129
No log	2.1481	58	1.0988	0.4873	1.0988	1.0482
No log	2.2222	60	0.9580	0.5729	0.9580	0.9788
No log	2.2963	62	0.7144	0.6757	0.7144	0.8452
No log	2.3704	64	0.6091	0.6978	0.6091	0.7804
No log	2.4444	66	0.5992	0.7128	0.5992	0.7741
No log	2.5185	68	0.6087	0.6974	0.6087	0.7802
No log	2.5926	70	0.6546	0.7242	0.6546	0.8091
No log	2.6667	72	0.7628	0.6996	0.7628	0.8734
No log	2.7407	74	0.8404	0.6640	0.8404	0.9167
No log	2.8148	76	0.7312	0.6986	0.7312	0.8551
No log	2.8889	78	0.5846	0.7156	0.5846	0.7646
No log	2.9630	80	0.5931	0.7405	0.5931	0.7701
No log	3.0370	82	0.5984	0.7194	0.5984	0.7736
No log	3.1111	84	0.6390	0.7232	0.6390	0.7994
No log	3.1852	86	0.6293	0.7138	0.6293	0.7933
No log	3.2593	88	0.6345	0.7237	0.6345	0.7966
No log	3.3333	90	0.6548	0.7264	0.6548	0.8092
No log	3.4074	92	0.6363	0.7283	0.6363	0.7977
No log	3.4815	94	0.7182	0.7006	0.7182	0.8475
No log	3.5556	96	0.7308	0.6952	0.7308	0.8549
No log	3.6296	98	0.6936	0.7323	0.6936	0.8328
No log	3.7037	100	0.6844	0.7309	0.6844	0.8273
No log	3.7778	102	0.6750	0.7098	0.6750	0.8216
No log	3.8519	104	0.6398	0.7218	0.6398	0.7999
No log	3.9259	106	0.6519	0.7249	0.6519	0.8074
No log	4.0	108	0.7795	0.6624	0.7795	0.8829
No log	4.0741	110	0.8278	0.6207	0.8278	0.9098
No log	4.1481	112	0.7134	0.6557	0.7134	0.8446
No log	4.2222	114	0.5943	0.7318	0.5943	0.7709
No log	4.2963	116	0.6336	0.7236	0.6336	0.7960
No log	4.3704	118	0.7475	0.6933	0.7475	0.8646
No log	4.4444	120	0.7108	0.6905	0.7108	0.8431
No log	4.5185	122	0.6039	0.7338	0.6039	0.7771
No log	4.5926	124	0.6413	0.6999	0.6413	0.8008
No log	4.6667	126	0.8019	0.6121	0.8019	0.8955
No log	4.7407	128	0.8454	0.6226	0.8454	0.9194
No log	4.8148	130	0.7216	0.6800	0.7216	0.8495
No log	4.8889	132	0.6179	0.7297	0.6179	0.7860
No log	4.9630	134	0.7216	0.7	0.7216	0.8495
No log	5.0370	136	0.8568	0.6733	0.8568	0.9256
No log	5.1111	138	0.8561	0.6733	0.8561	0.9253
No log	5.1852	140	0.7512	0.7021	0.7512	0.8667
No log	5.2593	142	0.6556	0.7262	0.6556	0.8097
No log	5.3333	144	0.6516	0.7244	0.6516	0.8072
No log	5.4074	146	0.6525	0.7102	0.6525	0.8078
No log	5.4815	148	0.6273	0.7273	0.6273	0.7920
No log	5.5556	150	0.6172	0.7527	0.6172	0.7856
No log	5.6296	152	0.6142	0.7338	0.6142	0.7837
No log	5.7037	154	0.6127	0.7395	0.6127	0.7828
No log	5.7778	156	0.6243	0.7231	0.6243	0.7901
No log	5.8519	158	0.6385	0.7278	0.6385	0.7991
No log	5.9259	160	0.6678	0.7194	0.6678	0.8172
No log	6.0	162	0.6876	0.7005	0.6876	0.8292
No log	6.0741	164	0.6696	0.7324	0.6696	0.8183
No log	6.1481	166	0.6737	0.7470	0.6737	0.8208
No log	6.2222	168	0.6953	0.7392	0.6953	0.8339
No log	6.2963	170	0.6936	0.7378	0.6936	0.8328
No log	6.3704	172	0.6638	0.7327	0.6638	0.8147
No log	6.4444	174	0.6384	0.7223	0.6384	0.7990
No log	6.5185	176	0.6644	0.6891	0.6644	0.8151
No log	6.5926	178	0.6748	0.6902	0.6748	0.8215
No log	6.6667	180	0.6312	0.7311	0.6312	0.7945
No log	6.7407	182	0.6012	0.7303	0.6012	0.7754
No log	6.8148	184	0.5991	0.7472	0.5991	0.7740
No log	6.8889	186	0.6206	0.7343	0.6206	0.7878
No log	6.9630	188	0.6198	0.7148	0.6198	0.7873
No log	7.0370	190	0.5977	0.7495	0.5977	0.7731
No log	7.1111	192	0.6000	0.7419	0.6000	0.7746
No log	7.1852	194	0.6047	0.7364	0.6047	0.7776
No log	7.2593	196	0.6030	0.7381	0.6030	0.7765
No log	7.3333	198	0.6265	0.7357	0.6265	0.7915
No log	7.4074	200	0.6420	0.7556	0.6420	0.8013
No log	7.4815	202	0.6333	0.7357	0.6333	0.7958
No log	7.5556	204	0.6187	0.7258	0.6187	0.7866
No log	7.6296	206	0.6250	0.7267	0.6250	0.7906
No log	7.7037	208	0.6364	0.7283	0.6364	0.7977
No log	7.7778	210	0.6522	0.7089	0.6522	0.8076
No log	7.8519	212	0.6577	0.7102	0.6577	0.8110
No log	7.9259	214	0.6579	0.7113	0.6579	0.8111
No log	8.0	216	0.6608	0.6992	0.6608	0.8129
No log	8.0741	218	0.6577	0.7257	0.6577	0.8110
No log	8.1481	220	0.6569	0.7200	0.6569	0.8105
No log	8.2222	222	0.6599	0.7105	0.6599	0.8124
No log	8.2963	224	0.6617	0.7105	0.6617	0.8135
No log	8.3704	226	0.6611	0.6946	0.6611	0.8131
No log	8.4444	228	0.6587	0.7157	0.6587	0.8116
No log	8.5185	230	0.6554	0.7157	0.6554	0.8096
No log	8.5926	232	0.6554	0.7157	0.6554	0.8096
No log	8.6667	234	0.6553	0.7207	0.6553	0.8095
No log	8.7407	236	0.6597	0.6988	0.6597	0.8122
No log	8.8148	238	0.6638	0.6885	0.6638	0.8148
No log	8.8889	240	0.6623	0.6885	0.6623	0.8138
No log	8.9630	242	0.6568	0.7024	0.6568	0.8105
No log	9.0370	244	0.6501	0.7165	0.6501	0.8063
No log	9.1111	246	0.6456	0.7248	0.6456	0.8035
No log	9.1852	248	0.6463	0.7281	0.6463	0.8039
No log	9.2593	250	0.6482	0.7250	0.6482	0.8051
No log	9.3333	252	0.6479	0.7308	0.6479	0.8049
No log	9.4074	254	0.6451	0.7308	0.6451	0.8032
No log	9.4815	256	0.6425	0.7340	0.6425	0.8015
No log	9.5556	258	0.6410	0.7255	0.6410	0.8006
No log	9.6296	260	0.6407	0.7157	0.6407	0.8004
No log	9.7037	262	0.6404	0.7115	0.6404	0.8003
No log	9.7778	264	0.6402	0.7073	0.6402	0.8001
No log	9.8519	266	0.6398	0.7073	0.6398	0.7999
No log	9.9259	268	0.6396	0.7073	0.6396	0.7997
No log	10.0	270	0.6395	0.7073	0.6395	0.7997

Framework versions

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