Arabic_FineTuningAraBERT_AugV0_k3_task1_organization_fold0

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: 0.6733
• Qwk: 0.7427
• Mse: 0.6733
• Rmse: 0.8205

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	5.0549	0.0011	5.0549	2.2483
No log	0.1429	4	2.7057	0.0985	2.7057	1.6449
No log	0.2143	6	1.7000	0.1582	1.7000	1.3038
No log	0.2857	8	1.2397	0.3793	1.2397	1.1134
No log	0.3571	10	1.1990	0.3462	1.1990	1.0950
No log	0.4286	12	1.1639	0.2939	1.1639	1.0789
No log	0.5	14	1.0559	0.2974	1.0559	1.0276
No log	0.5714	16	0.9991	0.3665	0.9991	0.9996
No log	0.6429	18	1.0775	0.5085	1.0775	1.0380
No log	0.7143	20	1.1749	0.5290	1.1749	1.0839
No log	0.7857	22	1.0649	0.5086	1.0649	1.0319
No log	0.8571	24	1.0232	0.5304	1.0232	1.0115
No log	0.9286	26	0.9246	0.5304	0.9246	0.9616
No log	1.0	28	0.8984	0.6143	0.8984	0.9478
No log	1.0714	30	0.8632	0.6143	0.8632	0.9291
No log	1.1429	32	0.9797	0.6100	0.9797	0.9898
No log	1.2143	34	0.9444	0.6060	0.9444	0.9718
No log	1.2857	36	0.7667	0.6503	0.7667	0.8756
No log	1.3571	38	0.7386	0.7232	0.7386	0.8594
No log	1.4286	40	0.6966	0.7525	0.6966	0.8346
No log	1.5	42	0.7423	0.6871	0.7423	0.8615
No log	1.5714	44	0.7053	0.7058	0.7053	0.8398
No log	1.6429	46	0.6488	0.7525	0.6488	0.8055
No log	1.7143	48	0.7536	0.6461	0.7536	0.8681
No log	1.7857	50	0.7396	0.6517	0.7396	0.8600
No log	1.8571	52	0.6893	0.6361	0.6893	0.8303
No log	1.9286	54	0.7666	0.6503	0.7666	0.8756
No log	2.0	56	1.0883	0.5273	1.0883	1.0432
No log	2.0714	58	1.5983	0.1054	1.5983	1.2642
No log	2.1429	60	1.6993	0.1363	1.6993	1.3036
No log	2.2143	62	1.2698	0.3636	1.2698	1.1268
No log	2.2857	64	0.8766	0.5532	0.8766	0.9363
No log	2.3571	66	0.7457	0.6143	0.7457	0.8636
No log	2.4286	68	0.7594	0.6503	0.7594	0.8714
No log	2.5	70	0.7683	0.6842	0.7683	0.8765
No log	2.5714	72	0.7347	0.7232	0.7347	0.8571
No log	2.6429	74	0.7850	0.7058	0.7850	0.8860
No log	2.7143	76	0.8892	0.6940	0.8892	0.9430
No log	2.7857	78	0.9128	0.6280	0.9128	0.9554
No log	2.8571	80	0.8893	0.6746	0.8893	0.9430
No log	2.9286	82	0.7909	0.6830	0.7909	0.8893
No log	3.0	84	0.7553	0.6830	0.7553	0.8691
No log	3.0714	86	0.7788	0.6363	0.7788	0.8825
No log	3.1429	88	0.8622	0.6115	0.8622	0.9285
No log	3.2143	90	0.8946	0.6115	0.8946	0.9458
No log	3.2857	92	0.8019	0.6972	0.8019	0.8955
No log	3.3571	94	0.6742	0.6830	0.6742	0.8211
No log	3.4286	96	0.6570	0.6830	0.6570	0.8106
No log	3.5	98	0.6634	0.7058	0.6634	0.8145
No log	3.5714	100	0.8008	0.7504	0.8008	0.8949
No log	3.6429	102	0.8772	0.6117	0.8772	0.9366
No log	3.7143	104	0.7695	0.6786	0.7695	0.8772
No log	3.7857	106	0.6265	0.7603	0.6265	0.7915
No log	3.8571	108	0.5754	0.7898	0.5754	0.7586
No log	3.9286	110	0.5755	0.7898	0.5755	0.7586
No log	4.0	112	0.6409	0.7603	0.6409	0.8006
No log	4.0714	114	0.7370	0.5777	0.7370	0.8585
No log	4.1429	116	0.6783	0.7216	0.6783	0.8236
No log	4.2143	118	0.5791	0.7417	0.5791	0.7610
No log	4.2857	120	0.5063	0.7898	0.5063	0.7116
No log	4.3571	122	0.4688	0.7327	0.4688	0.6847
No log	4.4286	124	0.4755	0.7327	0.4755	0.6896
No log	4.5	126	0.5228	0.7938	0.5228	0.7230
No log	4.5714	128	0.5609	0.7764	0.5609	0.7489
No log	4.6429	130	0.6445	0.7590	0.6445	0.8028
No log	4.7143	132	0.6361	0.7590	0.6361	0.7976
No log	4.7857	134	0.5655	0.7250	0.5655	0.7520
No log	4.8571	136	0.5630	0.7250	0.5630	0.7503
No log	4.9286	138	0.5357	0.7333	0.5357	0.7319
No log	5.0	140	0.5252	0.7157	0.5252	0.7247
No log	5.0714	142	0.5399	0.7157	0.5399	0.7348
No log	5.1429	144	0.5418	0.7517	0.5418	0.7361
No log	5.2143	146	0.6044	0.7586	0.6044	0.7774
No log	5.2857	148	0.6281	0.7586	0.6281	0.7925
No log	5.3571	150	0.6101	0.7586	0.6101	0.7811
No log	5.4286	152	0.5938	0.7586	0.5938	0.7706
No log	5.5	154	0.5466	0.7429	0.5466	0.7393
No log	5.5714	156	0.5238	0.7429	0.5238	0.7238
No log	5.6429	158	0.5230	0.7429	0.5230	0.7232
No log	5.7143	160	0.5558	0.7178	0.5558	0.7456
No log	5.7857	162	0.6161	0.7009	0.6161	0.7849
No log	5.8571	164	0.6358	0.7038	0.6358	0.7974
No log	5.9286	166	0.6488	0.7038	0.6488	0.8055
No log	6.0	168	0.6204	0.7511	0.6204	0.7877
No log	6.0714	170	0.5950	0.7594	0.5950	0.7714
No log	6.1429	172	0.5922	0.7602	0.5922	0.7696
No log	6.2143	174	0.5933	0.7602	0.5933	0.7703
No log	6.2857	176	0.5929	0.7775	0.5929	0.7700
No log	6.3571	178	0.6336	0.7775	0.6336	0.7960
No log	6.4286	180	0.7250	0.7038	0.7250	0.8515
No log	6.5	182	0.8433	0.6760	0.8433	0.9183
No log	6.5714	184	0.8694	0.6760	0.8694	0.9324
No log	6.6429	186	0.8376	0.6716	0.8376	0.9152
No log	6.7143	188	0.7636	0.6938	0.7636	0.8738
No log	6.7857	190	0.7226	0.7250	0.7226	0.8501
No log	6.8571	192	0.7105	0.7420	0.7105	0.8429
No log	6.9286	194	0.6798	0.7594	0.6798	0.8245
No log	7.0	196	0.6944	0.7745	0.6944	0.8333
No log	7.0714	198	0.7359	0.7658	0.7359	0.8578
No log	7.1429	200	0.7269	0.7273	0.7269	0.8526
No log	7.2143	202	0.6949	0.7819	0.6949	0.8336
No log	7.2857	204	0.6601	0.7678	0.6601	0.8125
No log	7.3571	206	0.6255	0.7182	0.6255	0.7909
No log	7.4286	208	0.6185	0.7350	0.6185	0.7865
No log	7.5	210	0.6120	0.7350	0.6120	0.7823
No log	7.5714	212	0.6065	0.7350	0.6065	0.7788
No log	7.6429	214	0.6087	0.7182	0.6087	0.7802
No log	7.7143	216	0.6264	0.7014	0.6264	0.7915
No log	7.7857	218	0.6490	0.7510	0.6490	0.8056
No log	7.8571	220	0.6458	0.7014	0.6458	0.8036
No log	7.9286	222	0.6349	0.7014	0.6349	0.7968
No log	8.0	224	0.6333	0.7182	0.6333	0.7958
No log	8.0714	226	0.6454	0.7014	0.6454	0.8034
No log	8.1429	228	0.6572	0.7014	0.6572	0.8107
No log	8.2143	230	0.6740	0.7106	0.6740	0.8210
No log	8.2857	232	0.6903	0.7504	0.6903	0.8309
No log	8.3571	234	0.6801	0.6738	0.6801	0.8247
No log	8.4286	236	0.6545	0.7014	0.6545	0.8090
No log	8.5	238	0.6319	0.7429	0.6319	0.7949
No log	8.5714	240	0.6242	0.7429	0.6242	0.7901
No log	8.6429	242	0.6290	0.7429	0.6290	0.7931
No log	8.7143	244	0.6318	0.7429	0.6318	0.7949
No log	8.7857	246	0.6435	0.7429	0.6435	0.8022
No log	8.8571	248	0.6644	0.7157	0.6644	0.8151
No log	8.9286	250	0.7006	0.7038	0.7006	0.8370
No log	9.0	252	0.7446	0.7081	0.7446	0.8629
No log	9.0714	254	0.7804	0.7081	0.7804	0.8834
No log	9.1429	256	0.7911	0.7081	0.7911	0.8894
No log	9.2143	258	0.7857	0.7081	0.7857	0.8864
No log	9.2857	260	0.7643	0.7059	0.7643	0.8743
No log	9.3571	262	0.7378	0.6620	0.7378	0.8589
No log	9.4286	264	0.7191	0.6620	0.7191	0.8480
No log	9.5	266	0.7094	0.6671	0.7094	0.8423
No log	9.5714	268	0.6989	0.7427	0.6989	0.8360
No log	9.6429	270	0.6882	0.7427	0.6882	0.8296
No log	9.7143	272	0.6811	0.7427	0.6811	0.8253
No log	9.7857	274	0.6757	0.7427	0.6757	0.8220
No log	9.8571	276	0.6738	0.7427	0.6738	0.8208
No log	9.9286	278	0.6730	0.7427	0.6730	0.8204
No log	10.0	280	0.6733	0.7427	0.6733	0.8205

Framework versions

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