ArabicNewSplits7_FineTuningAraBERT_noAug_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: 0.8148
• Qwk: 0.5039
• Mse: 0.8148
• Rmse: 0.9027

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.6667	2	4.3186	0.0289	4.3186	2.0781
No log	1.3333	4	3.5551	0.0057	3.5551	1.8855
No log	2.0	6	1.8715	0.1273	1.8715	1.3680
No log	2.6667	8	1.2768	0.1584	1.2768	1.1300
No log	3.3333	10	1.2187	0.1043	1.2187	1.1039
No log	4.0	12	1.1801	0.0802	1.1801	1.0863
No log	4.6667	14	1.2251	0.1582	1.2251	1.1068
No log	5.3333	16	1.1674	0.2255	1.1674	1.0805
No log	6.0	18	1.1509	0.2499	1.1509	1.0728
No log	6.6667	20	1.2198	0.4300	1.2198	1.1045
No log	7.3333	22	1.3491	0.3803	1.3491	1.1615
No log	8.0	24	1.0753	0.4596	1.0753	1.0369
No log	8.6667	26	0.9661	0.4521	0.9661	0.9829
No log	9.3333	28	1.0907	0.3935	1.0907	1.0444
No log	10.0	30	0.9408	0.4343	0.9408	0.9699
No log	10.6667	32	0.9663	0.4707	0.9663	0.9830
No log	11.3333	34	1.0112	0.4635	1.0112	1.0056
No log	12.0	36	1.0787	0.3988	1.0787	1.0386
No log	12.6667	38	1.0302	0.4099	1.0302	1.0150
No log	13.3333	40	0.9790	0.4314	0.9790	0.9894
No log	14.0	42	0.9711	0.4948	0.9711	0.9854
No log	14.6667	44	0.9074	0.5161	0.9074	0.9526
No log	15.3333	46	0.8885	0.5232	0.8885	0.9426
No log	16.0	48	0.9216	0.5392	0.9216	0.9600
No log	16.6667	50	0.8836	0.5232	0.8836	0.9400
No log	17.3333	52	0.8689	0.4802	0.8689	0.9322
No log	18.0	54	0.8673	0.5253	0.8673	0.9313
No log	18.6667	56	0.8704	0.5578	0.8704	0.9330
No log	19.3333	58	0.8229	0.6026	0.8229	0.9071
No log	20.0	60	0.8022	0.5750	0.8022	0.8956
No log	20.6667	62	0.8539	0.5893	0.8539	0.9241
No log	21.3333	64	0.8078	0.5911	0.8078	0.8988
No log	22.0	66	0.8441	0.5892	0.8441	0.9188
No log	22.6667	68	0.8423	0.5920	0.8423	0.9178
No log	23.3333	70	0.7835	0.5713	0.7835	0.8851
No log	24.0	72	0.8156	0.6142	0.8156	0.9031
No log	24.6667	74	0.9345	0.4760	0.9345	0.9667
No log	25.3333	76	0.9119	0.5232	0.9119	0.9550
No log	26.0	78	0.8000	0.6001	0.8000	0.8944
No log	26.6667	80	0.7924	0.6176	0.7924	0.8902
No log	27.3333	82	0.8462	0.4998	0.8462	0.9199
No log	28.0	84	0.9201	0.5210	0.9201	0.9592
No log	28.6667	86	0.9072	0.4852	0.9072	0.9525
No log	29.3333	88	0.8669	0.4802	0.8669	0.9311
No log	30.0	90	0.8311	0.5969	0.8311	0.9117
No log	30.6667	92	0.8143	0.5969	0.8143	0.9024
No log	31.3333	94	0.8059	0.5530	0.8059	0.8977
No log	32.0	96	0.8161	0.5253	0.8161	0.9034
No log	32.6667	98	0.9138	0.5224	0.9138	0.9559
No log	33.3333	100	0.9289	0.5027	0.9289	0.9638
No log	34.0	102	0.8859	0.5637	0.8859	0.9412
No log	34.6667	104	0.8473	0.5659	0.8473	0.9205
No log	35.3333	106	0.8790	0.5714	0.8790	0.9375
No log	36.0	108	0.8788	0.4976	0.8788	0.9375
No log	36.6667	110	0.8245	0.5498	0.8245	0.9080
No log	37.3333	112	0.8194	0.5601	0.8194	0.9052
No log	38.0	114	0.8635	0.5306	0.8635	0.9293
No log	38.6667	116	0.8913	0.5532	0.8913	0.9441
No log	39.3333	118	0.8816	0.5141	0.8816	0.9390
No log	40.0	120	0.8785	0.5028	0.8785	0.9373
No log	40.6667	122	0.8887	0.5495	0.8887	0.9427
No log	41.3333	124	0.8889	0.5659	0.8889	0.9428
No log	42.0	126	0.9451	0.5623	0.9451	0.9721
No log	42.6667	128	0.9728	0.5236	0.9728	0.9863
No log	43.3333	130	0.9759	0.5175	0.9759	0.9879
No log	44.0	132	0.9280	0.5182	0.9280	0.9633
No log	44.6667	134	0.9013	0.5223	0.9013	0.9494
No log	45.3333	136	0.8603	0.5440	0.8603	0.9275
No log	46.0	138	0.8540	0.5272	0.8540	0.9241
No log	46.6667	140	0.8759	0.5028	0.8759	0.9359
No log	47.3333	142	0.9440	0.4615	0.9440	0.9716
No log	48.0	144	1.0623	0.4384	1.0623	1.0307
No log	48.6667	146	1.0527	0.4384	1.0527	1.0260
No log	49.3333	148	0.9734	0.4395	0.9734	0.9866
No log	50.0	150	0.8808	0.5041	0.8808	0.9385
No log	50.6667	152	0.8440	0.5298	0.8440	0.9187
No log	51.3333	154	0.8417	0.5298	0.8417	0.9175
No log	52.0	156	0.8425	0.5185	0.8425	0.9179
No log	52.6667	158	0.8137	0.4794	0.8137	0.9020
No log	53.3333	160	0.7995	0.4521	0.7995	0.8942
No log	54.0	162	0.8230	0.5202	0.8230	0.9072
No log	54.6667	164	0.8890	0.4902	0.8890	0.9428
No log	55.3333	166	0.9673	0.4138	0.9673	0.9835
No log	56.0	168	0.9871	0.4215	0.9871	0.9935
No log	56.6667	170	1.0499	0.4368	1.0499	1.0246
No log	57.3333	172	1.0152	0.4368	1.0152	1.0076
No log	58.0	174	0.9268	0.4327	0.9268	0.9627
No log	58.6667	176	0.8770	0.5068	0.8770	0.9365
No log	59.3333	178	0.8835	0.5094	0.8835	0.9399
No log	60.0	180	0.8853	0.5249	0.8853	0.9409
No log	60.6667	182	0.8935	0.5063	0.8935	0.9452
No log	61.3333	184	0.9249	0.4658	0.9249	0.9617
No log	62.0	186	0.9280	0.4852	0.9280	0.9633
No log	62.6667	188	0.9216	0.4658	0.9216	0.9600
No log	63.3333	190	0.8901	0.4857	0.8901	0.9434
No log	64.0	192	0.8718	0.4883	0.8718	0.9337
No log	64.6667	194	0.8694	0.5109	0.8694	0.9324
No log	65.3333	196	0.9065	0.4960	0.9065	0.9521
No log	66.0	198	0.9170	0.4551	0.9170	0.9576
No log	66.6667	200	0.9124	0.4551	0.9124	0.9552
No log	67.3333	202	0.9320	0.4199	0.9320	0.9654
No log	68.0	204	0.9537	0.4271	0.9537	0.9766
No log	68.6667	206	0.9358	0.4534	0.9358	0.9673
No log	69.3333	208	0.8876	0.4788	0.8876	0.9421
No log	70.0	210	0.8288	0.5539	0.8288	0.9104
No log	70.6667	212	0.8034	0.5211	0.8034	0.8963
No log	71.3333	214	0.7787	0.5437	0.7787	0.8824
No log	72.0	216	0.7729	0.6088	0.7729	0.8791
No log	72.6667	218	0.7823	0.5836	0.7823	0.8845
No log	73.3333	220	0.7830	0.5836	0.7830	0.8849
No log	74.0	222	0.7833	0.5624	0.7833	0.8850
No log	74.6667	224	0.7724	0.5864	0.7724	0.8789
No log	75.3333	226	0.7738	0.5864	0.7738	0.8797
No log	76.0	228	0.7821	0.5624	0.7821	0.8844
No log	76.6667	230	0.8024	0.5227	0.8024	0.8958
No log	77.3333	232	0.8258	0.5557	0.8258	0.9087
No log	78.0	234	0.8462	0.5370	0.8462	0.9199
No log	78.6667	236	0.8389	0.5451	0.8389	0.9159
No log	79.3333	238	0.8142	0.5539	0.8142	0.9023
No log	80.0	240	0.8043	0.5756	0.8043	0.8968
No log	80.6667	242	0.7965	0.5920	0.7965	0.8925
No log	81.3333	244	0.7940	0.5332	0.7940	0.8911
No log	82.0	246	0.7946	0.5726	0.7946	0.8914
No log	82.6667	248	0.7879	0.5726	0.7879	0.8877
No log	83.3333	250	0.7780	0.5827	0.7780	0.8821
No log	84.0	252	0.7687	0.6358	0.7687	0.8768
No log	84.6667	254	0.7729	0.5886	0.7729	0.8792
No log	85.3333	256	0.7873	0.5564	0.7873	0.8873
No log	86.0	258	0.7928	0.5351	0.7928	0.8904
No log	86.6667	260	0.8028	0.5053	0.8028	0.8960
No log	87.3333	262	0.8146	0.5394	0.8146	0.9025
No log	88.0	264	0.8174	0.5394	0.8174	0.9041
No log	88.6667	266	0.8062	0.5682	0.8062	0.8979
No log	89.3333	268	0.8001	0.5351	0.8001	0.8945
No log	90.0	270	0.7951	0.5370	0.7951	0.8917
No log	90.6667	272	0.7934	0.5370	0.7934	0.8907
No log	91.3333	274	0.7932	0.5370	0.7932	0.8906
No log	92.0	276	0.7995	0.5370	0.7995	0.8942
No log	92.6667	278	0.8080	0.5039	0.8080	0.8989
No log	93.3333	280	0.8145	0.5039	0.8145	0.9025
No log	94.0	282	0.8162	0.5039	0.8162	0.9035
No log	94.6667	284	0.8131	0.5039	0.8131	0.9017
No log	95.3333	286	0.8082	0.5039	0.8082	0.8990
No log	96.0	288	0.8050	0.5039	0.8050	0.8972
No log	96.6667	290	0.8048	0.5039	0.8048	0.8971
No log	97.3333	292	0.8077	0.5039	0.8077	0.8987
No log	98.0	294	0.8110	0.5039	0.8110	0.9005
No log	98.6667	296	0.8139	0.5039	0.8139	0.9022
No log	99.3333	298	0.8148	0.5039	0.8148	0.9027
No log	100.0	300	0.8148	0.5039	0.8148	0.9027

Framework versions

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