ArabicNewSplits4_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k9_task5_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: 0.7290
• Qwk: 0.7446
• Mse: 0.7290
• Rmse: 0.8538

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	0.0625	2	2.3218	0.0448	2.3218	1.5237
No log	0.125	4	1.5170	0.1988	1.5170	1.2317
No log	0.1875	6	1.5629	0.0758	1.5629	1.2502
No log	0.25	8	1.5273	0.1564	1.5273	1.2358
No log	0.3125	10	1.5227	0.3162	1.5227	1.2340
No log	0.375	12	1.6012	0.2685	1.6012	1.2654
No log	0.4375	14	1.6605	0.2885	1.6605	1.2886
No log	0.5	16	1.6607	0.2859	1.6607	1.2887
No log	0.5625	18	1.8676	0.2789	1.8676	1.3666
No log	0.625	20	2.1771	0.3352	2.1771	1.4755
No log	0.6875	22	2.1874	0.3281	2.1874	1.4790
No log	0.75	24	1.5733	0.2995	1.5733	1.2543
No log	0.8125	26	1.3107	0.2063	1.3107	1.1449
No log	0.875	28	1.1809	0.2957	1.1809	1.0867
No log	0.9375	30	1.0911	0.2942	1.0911	1.0446
No log	1.0	32	1.0317	0.4114	1.0317	1.0157
No log	1.0625	34	1.1497	0.4128	1.1497	1.0722
No log	1.125	36	1.5620	0.4480	1.5620	1.2498
No log	1.1875	38	1.7201	0.4313	1.7201	1.3115
No log	1.25	40	1.4205	0.5062	1.4205	1.1918
No log	1.3125	42	0.9588	0.5514	0.9588	0.9792
No log	1.375	44	0.7429	0.6371	0.7429	0.8619
No log	1.4375	46	0.8194	0.5223	0.8194	0.9052
No log	1.5	48	0.8174	0.5245	0.8174	0.9041
No log	1.5625	50	0.6657	0.6883	0.6657	0.8159
No log	1.625	52	0.6548	0.7194	0.6548	0.8092
No log	1.6875	54	0.6691	0.7387	0.6691	0.8180
No log	1.75	56	0.6221	0.7125	0.6221	0.7887
No log	1.8125	58	0.6147	0.7219	0.6147	0.7840
No log	1.875	60	0.7175	0.7333	0.7175	0.8471
No log	1.9375	62	0.9262	0.6552	0.9262	0.9624
No log	2.0	64	0.9048	0.6750	0.9048	0.9512
No log	2.0625	66	0.8528	0.6951	0.8528	0.9234
No log	2.125	68	0.9206	0.6873	0.9206	0.9595
No log	2.1875	70	1.1309	0.6142	1.1309	1.0634
No log	2.25	72	1.0827	0.6151	1.0827	1.0406
No log	2.3125	74	0.8945	0.6915	0.8945	0.9458
No log	2.375	76	0.9747	0.6474	0.9747	0.9873
No log	2.4375	78	1.1342	0.6206	1.1342	1.0650
No log	2.5	80	1.0092	0.6601	1.0092	1.0046
No log	2.5625	82	0.9221	0.6816	0.9221	0.9603
No log	2.625	84	1.1323	0.6592	1.1323	1.0641
No log	2.6875	86	1.1922	0.6399	1.1922	1.0919
No log	2.75	88	0.9738	0.6491	0.9738	0.9868
No log	2.8125	90	0.6778	0.6995	0.6778	0.8233
No log	2.875	92	0.6095	0.7137	0.6095	0.7807
No log	2.9375	94	0.6130	0.7154	0.6130	0.7829
No log	3.0	96	0.7121	0.7150	0.7121	0.8439
No log	3.0625	98	0.9281	0.6687	0.9281	0.9634
No log	3.125	100	0.9630	0.6750	0.9630	0.9813
No log	3.1875	102	0.8444	0.6620	0.8444	0.9189
No log	3.25	104	0.6825	0.7188	0.6825	0.8261
No log	3.3125	106	0.6676	0.7233	0.6676	0.8171
No log	3.375	108	0.7321	0.7142	0.7321	0.8556
No log	3.4375	110	0.8523	0.6757	0.8523	0.9232
No log	3.5	112	0.9205	0.6579	0.9205	0.9594
No log	3.5625	114	0.9225	0.6563	0.9225	0.9605
No log	3.625	116	1.1092	0.6623	1.1092	1.0532
No log	3.6875	118	1.1180	0.6630	1.1180	1.0573
No log	3.75	120	0.9594	0.6467	0.9594	0.9795
No log	3.8125	122	0.7492	0.6931	0.7492	0.8655
No log	3.875	124	0.6937	0.7333	0.6937	0.8329
No log	3.9375	126	0.7164	0.7164	0.7164	0.8464
No log	4.0	128	0.7927	0.6914	0.7927	0.8904
No log	4.0625	130	0.7680	0.6876	0.7680	0.8764
No log	4.125	132	0.7108	0.7339	0.7108	0.8431
No log	4.1875	134	0.6707	0.7588	0.6707	0.8190
No log	4.25	136	0.6802	0.7666	0.6802	0.8247
No log	4.3125	138	0.7908	0.7000	0.7908	0.8893
No log	4.375	140	0.9018	0.6757	0.9018	0.9496
No log	4.4375	142	0.8648	0.6752	0.8648	0.9299
No log	4.5	144	0.7510	0.7165	0.7510	0.8666
No log	4.5625	146	0.6945	0.7492	0.6945	0.8334
No log	4.625	148	0.7187	0.7389	0.7187	0.8478
No log	4.6875	150	0.7425	0.7389	0.7425	0.8617
No log	4.75	152	0.7068	0.7495	0.7068	0.8407
No log	4.8125	154	0.6567	0.7551	0.6567	0.8104
No log	4.875	156	0.6811	0.7440	0.6811	0.8253
No log	4.9375	158	0.7104	0.7271	0.7104	0.8429
No log	5.0	160	0.7119	0.7271	0.7119	0.8438
No log	5.0625	162	0.6732	0.7507	0.6732	0.8205
No log	5.125	164	0.6957	0.7511	0.6957	0.8341
No log	5.1875	166	0.7402	0.7195	0.7402	0.8604
No log	5.25	168	0.7519	0.7098	0.7519	0.8671
No log	5.3125	170	0.8077	0.6724	0.8077	0.8987
No log	5.375	172	0.8068	0.6852	0.8068	0.8982
No log	5.4375	174	0.7493	0.7183	0.7493	0.8656
No log	5.5	176	0.7290	0.7264	0.7290	0.8538
No log	5.5625	178	0.7726	0.6904	0.7726	0.8790
No log	5.625	180	0.8053	0.6813	0.8053	0.8974
No log	5.6875	182	0.7426	0.7224	0.7426	0.8617
No log	5.75	184	0.6484	0.7536	0.6484	0.8052
No log	5.8125	186	0.6282	0.7564	0.6282	0.7926
No log	5.875	188	0.6558	0.7534	0.6558	0.8098
No log	5.9375	190	0.7776	0.7280	0.7776	0.8818
No log	6.0	192	0.9884	0.6395	0.9884	0.9942
No log	6.0625	194	1.0840	0.6301	1.0840	1.0412
No log	6.125	196	1.0493	0.6301	1.0493	1.0243
No log	6.1875	198	0.9233	0.6507	0.9233	0.9609
No log	6.25	200	0.7893	0.7190	0.7893	0.8884
No log	6.3125	202	0.7455	0.7217	0.7455	0.8634
No log	6.375	204	0.7439	0.7175	0.7439	0.8625
No log	6.4375	206	0.8109	0.7141	0.8109	0.9005
No log	6.5	208	0.8679	0.6816	0.8679	0.9316
No log	6.5625	210	0.9181	0.6520	0.9181	0.9582
No log	6.625	212	0.8927	0.6655	0.8927	0.9448
No log	6.6875	214	0.8409	0.6953	0.8409	0.9170
No log	6.75	216	0.7775	0.7338	0.7775	0.8818
No log	6.8125	218	0.7615	0.7380	0.7615	0.8726
No log	6.875	220	0.7519	0.7402	0.7519	0.8671
No log	6.9375	222	0.7415	0.7445	0.7415	0.8611
No log	7.0	224	0.7117	0.7279	0.7117	0.8436
No log	7.0625	226	0.6942	0.7423	0.6942	0.8332
No log	7.125	228	0.6731	0.7540	0.6731	0.8204
No log	7.1875	230	0.6844	0.7537	0.6844	0.8273
No log	7.25	232	0.7156	0.7418	0.7156	0.8459
No log	7.3125	234	0.7214	0.7418	0.7214	0.8493
No log	7.375	236	0.7243	0.7418	0.7243	0.8511
No log	7.4375	238	0.7354	0.7266	0.7354	0.8576
No log	7.5	240	0.7154	0.7140	0.7154	0.8458
No log	7.5625	242	0.6936	0.7642	0.6936	0.8328
No log	7.625	244	0.6558	0.7684	0.6558	0.8098
No log	7.6875	246	0.6466	0.7756	0.6466	0.8041
No log	7.75	248	0.6280	0.7708	0.6280	0.7924
No log	7.8125	250	0.6034	0.7621	0.6034	0.7768
No log	7.875	252	0.5905	0.7544	0.5905	0.7685
No log	7.9375	254	0.5943	0.7582	0.5943	0.7709
No log	8.0	256	0.6166	0.7470	0.6166	0.7853
No log	8.0625	258	0.6605	0.7568	0.6605	0.8127
No log	8.125	260	0.7348	0.7402	0.7348	0.8572
No log	8.1875	262	0.7969	0.7089	0.7969	0.8927
No log	8.25	264	0.8149	0.7006	0.8149	0.9027
No log	8.3125	266	0.7948	0.7166	0.7948	0.8915
No log	8.375	268	0.7471	0.7384	0.7471	0.8644
No log	8.4375	270	0.6943	0.7583	0.6943	0.8333
No log	8.5	272	0.6554	0.7498	0.6554	0.8096
No log	8.5625	274	0.6363	0.7540	0.6363	0.7977
No log	8.625	276	0.6384	0.7540	0.6384	0.7990
No log	8.6875	278	0.6533	0.7540	0.6533	0.8083
No log	8.75	280	0.6795	0.7495	0.6795	0.8243
No log	8.8125	282	0.6947	0.7495	0.6947	0.8335
No log	8.875	284	0.7108	0.7505	0.7108	0.8431
No log	8.9375	286	0.7228	0.7518	0.7228	0.8502
No log	9.0	288	0.7359	0.7588	0.7359	0.8578
No log	9.0625	290	0.7399	0.7488	0.7399	0.8602
No log	9.125	292	0.7337	0.7488	0.7337	0.8565
No log	9.1875	294	0.7238	0.7510	0.7238	0.8508
No log	9.25	296	0.7208	0.7510	0.7208	0.8490
No log	9.3125	298	0.7227	0.7545	0.7227	0.8501
No log	9.375	300	0.7301	0.7446	0.7301	0.8545
No log	9.4375	302	0.7303	0.7446	0.7303	0.8546
No log	9.5	304	0.7365	0.7425	0.7365	0.8582
No log	9.5625	306	0.7409	0.7425	0.7409	0.8608
No log	9.625	308	0.7461	0.7425	0.7461	0.8638
No log	9.6875	310	0.7468	0.7425	0.7468	0.8642
No log	9.75	312	0.7420	0.7425	0.7420	0.8614
No log	9.8125	314	0.7367	0.7425	0.7367	0.8583
No log	9.875	316	0.7327	0.7425	0.7327	0.8560
No log	9.9375	318	0.7302	0.7446	0.7302	0.8545
No log	10.0	320	0.7290	0.7446	0.7290	0.8538

Framework versions

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