ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k4_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: 0.6303
• Qwk: 0.7137
• Mse: 0.6303
• Rmse: 0.7939

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	5.2711	-0.0179	5.2711	2.2959
No log	0.1538	4	3.0938	0.0908	3.0938	1.7589
No log	0.2308	6	2.0444	0.1627	2.0444	1.4298
No log	0.3077	8	1.5483	0.1037	1.5483	1.2443
No log	0.3846	10	1.3053	0.2940	1.3053	1.1425
No log	0.4615	12	1.1140	0.2072	1.1140	1.0555
No log	0.5385	14	1.0280	0.3848	1.0280	1.0139
No log	0.6154	16	1.4314	0.2086	1.4314	1.1964
No log	0.6923	18	1.5259	0.1732	1.5259	1.2353
No log	0.7692	20	1.1320	0.3796	1.1320	1.0639
No log	0.8462	22	0.9137	0.3917	0.9137	0.9559
No log	0.9231	24	0.8826	0.4306	0.8826	0.9395
No log	1.0	26	0.9864	0.3573	0.9864	0.9932
No log	1.0769	28	1.2875	0.3430	1.2875	1.1347
No log	1.1538	30	1.1316	0.3890	1.1316	1.0638
No log	1.2308	32	0.9021	0.4694	0.9021	0.9498
No log	1.3077	34	0.9150	0.4398	0.9150	0.9566
No log	1.3846	36	1.3233	0.3904	1.3233	1.1504
No log	1.4615	38	1.5671	0.2970	1.5671	1.2518
No log	1.5385	40	1.2420	0.4084	1.2420	1.1145
No log	1.6154	42	0.9698	0.4768	0.9698	0.9848
No log	1.6923	44	0.8244	0.5252	0.8244	0.9079
No log	1.7692	46	0.7883	0.5589	0.7883	0.8879
No log	1.8462	48	0.8750	0.5052	0.8750	0.9354
No log	1.9231	50	0.9087	0.5065	0.9087	0.9532
No log	2.0	52	0.7461	0.6356	0.7461	0.8638
No log	2.0769	54	0.7501	0.6561	0.7501	0.8661
No log	2.1538	56	0.8300	0.6484	0.8300	0.9111
No log	2.2308	58	0.9158	0.6396	0.9158	0.9570
No log	2.3077	60	0.8389	0.6468	0.8389	0.9159
No log	2.3846	62	0.7197	0.6908	0.7197	0.8484
No log	2.4615	64	0.7443	0.7235	0.7443	0.8627
No log	2.5385	66	0.7336	0.7361	0.7336	0.8565
No log	2.6154	68	0.6811	0.7001	0.6811	0.8253
No log	2.6923	70	0.8887	0.6571	0.8887	0.9427
No log	2.7692	72	0.9960	0.5884	0.9960	0.9980
No log	2.8462	74	0.8945	0.6457	0.8945	0.9458
No log	2.9231	76	0.7266	0.7072	0.7266	0.8524
No log	3.0	78	0.6564	0.7058	0.6564	0.8102
No log	3.0769	80	0.6319	0.7391	0.6319	0.7949
No log	3.1538	82	0.6051	0.7033	0.6051	0.7779
No log	3.2308	84	0.6041	0.7269	0.6041	0.7772
No log	3.3077	86	0.7067	0.6748	0.7067	0.8406
No log	3.3846	88	0.7316	0.6575	0.7316	0.8553
No log	3.4615	90	0.7128	0.6810	0.7128	0.8443
No log	3.5385	92	0.6393	0.7196	0.6393	0.7995
No log	3.6154	94	0.6359	0.7279	0.6359	0.7974
No log	3.6923	96	0.6276	0.7034	0.6276	0.7922
No log	3.7692	98	0.6178	0.7262	0.6178	0.7860
No log	3.8462	100	0.6996	0.6931	0.6996	0.8364
No log	3.9231	102	0.7429	0.6794	0.7429	0.8619
No log	4.0	104	0.7562	0.6665	0.7562	0.8696
No log	4.0769	106	0.6112	0.7174	0.6112	0.7818
No log	4.1538	108	0.5484	0.7214	0.5484	0.7405
No log	4.2308	110	0.5706	0.7395	0.5706	0.7554
No log	4.3077	112	0.5618	0.7466	0.5618	0.7495
No log	4.3846	114	0.5755	0.7251	0.5755	0.7586
No log	4.4615	116	0.6411	0.7119	0.6411	0.8007
No log	4.5385	118	0.6823	0.7250	0.6823	0.8260
No log	4.6154	120	0.6434	0.7349	0.6434	0.8021
No log	4.6923	122	0.6149	0.7422	0.6149	0.7841
No log	4.7692	124	0.6392	0.7418	0.6392	0.7995
No log	4.8462	126	0.6730	0.7518	0.6730	0.8204
No log	4.9231	128	0.6635	0.7521	0.6635	0.8146
No log	5.0	130	0.6319	0.7407	0.6319	0.7949
No log	5.0769	132	0.6220	0.7287	0.6220	0.7886
No log	5.1538	134	0.5988	0.7193	0.5988	0.7738
No log	5.2308	136	0.5939	0.7326	0.5939	0.7707
No log	5.3077	138	0.6079	0.7373	0.6079	0.7797
No log	5.3846	140	0.6072	0.7373	0.6072	0.7792
No log	5.4615	142	0.6055	0.7546	0.6055	0.7781
No log	5.5385	144	0.6222	0.7448	0.6222	0.7888
No log	5.6154	146	0.6374	0.7485	0.6374	0.7984
No log	5.6923	148	0.6723	0.7500	0.6723	0.8199
No log	5.7692	150	0.7111	0.7362	0.7111	0.8433
No log	5.8462	152	0.7325	0.7220	0.7325	0.8558
No log	5.9231	154	0.6860	0.7160	0.6860	0.8283
No log	6.0	156	0.6366	0.7337	0.6366	0.7979
No log	6.0769	158	0.6202	0.7250	0.6202	0.7875
No log	6.1538	160	0.6304	0.7252	0.6304	0.7940
No log	6.2308	162	0.7002	0.6913	0.7002	0.8368
No log	6.3077	164	0.6609	0.6835	0.6609	0.8130
No log	6.3846	166	0.6095	0.7360	0.6095	0.7807
No log	6.4615	168	0.6492	0.7256	0.6492	0.8057
No log	6.5385	170	0.6800	0.7383	0.6800	0.8246
No log	6.6154	172	0.7008	0.7383	0.7008	0.8372
No log	6.6923	174	0.7213	0.7344	0.7213	0.8493
No log	6.7692	176	0.6721	0.7408	0.6721	0.8198
No log	6.8462	178	0.6479	0.7538	0.6479	0.8050
No log	6.9231	180	0.6499	0.7450	0.6499	0.8062
No log	7.0	182	0.6481	0.7450	0.6481	0.8050
No log	7.0769	184	0.6674	0.7241	0.6674	0.8169
No log	7.1538	186	0.7199	0.7418	0.7199	0.8485
No log	7.2308	188	0.7932	0.7060	0.7932	0.8906
No log	7.3077	190	0.8037	0.7018	0.8037	0.8965
No log	7.3846	192	0.7445	0.7165	0.7445	0.8628
No log	7.4615	194	0.6750	0.7256	0.6750	0.8216
No log	7.5385	196	0.6564	0.7181	0.6564	0.8102
No log	7.6154	198	0.6560	0.7404	0.6560	0.8099
No log	7.6923	200	0.6617	0.7295	0.6617	0.8135
No log	7.7692	202	0.6456	0.7404	0.6456	0.8035
No log	7.8462	204	0.6408	0.7089	0.6408	0.8005
No log	7.9231	206	0.6806	0.7311	0.6806	0.8250
No log	8.0	208	0.7166	0.7361	0.7166	0.8465
No log	8.0769	210	0.7327	0.7187	0.7327	0.8560
No log	8.1538	212	0.6958	0.7361	0.6958	0.8342
No log	8.2308	214	0.6514	0.7144	0.6514	0.8071
No log	8.3077	216	0.6252	0.7131	0.6252	0.7907
No log	8.3846	218	0.6213	0.7084	0.6213	0.7882
No log	8.4615	220	0.6281	0.7197	0.6281	0.7925
No log	8.5385	222	0.6226	0.7170	0.6226	0.7891
No log	8.6154	224	0.6171	0.7101	0.6171	0.7856
No log	8.6923	226	0.6341	0.7275	0.6341	0.7963
No log	8.7692	228	0.6739	0.7250	0.6739	0.8209
No log	8.8462	230	0.7226	0.7534	0.7226	0.8501
No log	8.9231	232	0.7404	0.7534	0.7404	0.8604
No log	9.0	234	0.7310	0.7534	0.7310	0.8550
No log	9.0769	236	0.7040	0.7374	0.7040	0.8391
No log	9.1538	238	0.6755	0.7250	0.6755	0.8219
No log	9.2308	240	0.6645	0.7250	0.6645	0.8152
No log	9.3077	242	0.6573	0.7256	0.6573	0.8107
No log	9.3846	244	0.6525	0.7276	0.6525	0.8077
No log	9.4615	246	0.6455	0.7378	0.6455	0.8035
No log	9.5385	248	0.6385	0.7322	0.6385	0.7990
No log	9.6154	250	0.6340	0.7251	0.6340	0.7962
No log	9.6923	252	0.6316	0.7251	0.6316	0.7947
No log	9.7692	254	0.6307	0.7195	0.6307	0.7942
No log	9.8462	256	0.6303	0.7137	0.6303	0.7939
No log	9.9231	258	0.6304	0.7137	0.6304	0.7940
No log	10.0	260	0.6303	0.7137	0.6303	0.7939

Framework versions

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