ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run2_AugV5_k1_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: 1.3040
• Qwk: 0.4333
• Mse: 1.3040
• Rmse: 1.1419

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	0.5	2	6.7981	0.0	6.7981	2.6073
No log	1.0	4	4.0288	0.0711	4.0288	2.0072
No log	1.5	6	2.7215	0.0387	2.7215	1.6497
No log	2.0	8	2.2475	0.0794	2.2475	1.4992
No log	2.5	10	1.6306	0.1538	1.6306	1.2769
No log	3.0	12	1.6539	0.1333	1.6539	1.2860
No log	3.5	14	1.6431	0.1538	1.6431	1.2818
No log	4.0	16	1.6724	0.1132	1.6724	1.2932
No log	4.5	18	1.5852	0.2202	1.5852	1.2590
No log	5.0	20	1.5690	0.2569	1.5690	1.2526
No log	5.5	22	1.5754	0.1495	1.5754	1.2551
No log	6.0	24	1.5574	0.2261	1.5574	1.2480
No log	6.5	26	1.5010	0.2712	1.5010	1.2252
No log	7.0	28	1.3508	0.3636	1.3508	1.1623
No log	7.5	30	1.3085	0.4194	1.3085	1.1439
No log	8.0	32	1.3988	0.3810	1.3988	1.1827
No log	8.5	34	1.2741	0.4462	1.2741	1.1288
No log	9.0	36	1.2323	0.5038	1.2323	1.1101
No log	9.5	38	1.2442	0.4848	1.2442	1.1155
No log	10.0	40	1.2879	0.4580	1.2879	1.1349
No log	10.5	42	1.3825	0.4444	1.3825	1.1758
No log	11.0	44	1.2960	0.4580	1.2960	1.1384
No log	11.5	46	1.3312	0.4806	1.3312	1.1538
No log	12.0	48	1.3210	0.4762	1.3210	1.1493
No log	12.5	50	1.3298	0.4462	1.3298	1.1532
No log	13.0	52	1.4165	0.3710	1.4165	1.1902
No log	13.5	54	1.2995	0.4375	1.2995	1.1400
No log	14.0	56	1.2846	0.4463	1.2846	1.1334
No log	14.5	58	1.4057	0.4677	1.4057	1.1856
No log	15.0	60	1.2948	0.5161	1.2948	1.1379
No log	15.5	62	1.1733	0.4806	1.1733	1.0832
No log	16.0	64	1.1718	0.4806	1.1718	1.0825
No log	16.5	66	1.1757	0.4806	1.1757	1.0843
No log	17.0	68	1.2512	0.48	1.2512	1.1186
No log	17.5	70	1.3135	0.4390	1.3135	1.1461
No log	18.0	72	1.2632	0.4688	1.2632	1.1239
No log	18.5	74	1.2673	0.5113	1.2673	1.1257
No log	19.0	76	1.2587	0.4341	1.2587	1.1219
No log	19.5	78	1.3898	0.4308	1.3898	1.1789
No log	20.0	80	1.4535	0.3871	1.4535	1.2056
No log	20.5	82	1.3252	0.4677	1.3252	1.1512
No log	21.0	84	1.2383	0.5156	1.2383	1.1128
No log	21.5	86	1.2516	0.4921	1.2516	1.1187
No log	22.0	88	1.3338	0.4426	1.3338	1.1549
No log	22.5	90	1.3761	0.4298	1.3761	1.1731
No log	23.0	92	1.3408	0.4426	1.3408	1.1579
No log	23.5	94	1.3593	0.4426	1.3593	1.1659
No log	24.0	96	1.3563	0.4167	1.3563	1.1646
No log	24.5	98	1.3083	0.4516	1.3083	1.1438
No log	25.0	100	1.3044	0.4603	1.3044	1.1421
No log	25.5	102	1.3025	0.4603	1.3025	1.1413
No log	26.0	104	1.2983	0.4531	1.2983	1.1394
No log	26.5	106	1.2946	0.4640	1.2946	1.1378
No log	27.0	108	1.3067	0.4640	1.3067	1.1431
No log	27.5	110	1.3213	0.4961	1.3213	1.1495
No log	28.0	112	1.3244	0.5312	1.3244	1.1508
No log	28.5	114	1.3245	0.4426	1.3245	1.1509
No log	29.0	116	1.3373	0.4034	1.3373	1.1564
No log	29.5	118	1.3292	0.4	1.3292	1.1529
No log	30.0	120	1.2743	0.4640	1.2743	1.1288
No log	30.5	122	1.2723	0.4882	1.2723	1.1279
No log	31.0	124	1.2795	0.4882	1.2795	1.1311
No log	31.5	126	1.3039	0.4	1.3039	1.1419
No log	32.0	128	1.4228	0.4553	1.4228	1.1928
No log	32.5	130	1.5202	0.3465	1.5202	1.2330
No log	33.0	132	1.4517	0.3902	1.4517	1.2049
No log	33.5	134	1.3440	0.4390	1.3440	1.1593
No log	34.0	136	1.3315	0.4961	1.3315	1.1539
No log	34.5	138	1.3384	0.4567	1.3384	1.1569
No log	35.0	140	1.3056	0.4961	1.3056	1.1426
No log	35.5	142	1.3169	0.4677	1.3169	1.1476
No log	36.0	144	1.3868	0.4426	1.3868	1.1776
No log	36.5	146	1.4018	0.4715	1.4018	1.1840
No log	37.0	148	1.3739	0.4426	1.3739	1.1721
No log	37.5	150	1.3322	0.4390	1.3322	1.1542
No log	38.0	152	1.3192	0.4567	1.3192	1.1486
No log	38.5	154	1.3384	0.4567	1.3384	1.1569
No log	39.0	156	1.3430	0.4677	1.3430	1.1589
No log	39.5	158	1.3794	0.4390	1.3794	1.1745
No log	40.0	160	1.4435	0.4320	1.4435	1.2015
No log	40.5	162	1.4995	0.4127	1.4995	1.2245
No log	41.0	164	1.5052	0.4409	1.5052	1.2269
No log	41.5	166	1.4356	0.3968	1.4356	1.1982
No log	42.0	168	1.3534	0.4286	1.3534	1.1633
No log	42.5	170	1.3067	0.4724	1.3067	1.1431
No log	43.0	172	1.3153	0.4320	1.3153	1.1469
No log	43.5	174	1.3785	0.4480	1.3785	1.1741
No log	44.0	176	1.3604	0.4480	1.3604	1.1664
No log	44.5	178	1.2848	0.4628	1.2848	1.1335
No log	45.0	180	1.2492	0.5041	1.2492	1.1177
No log	45.5	182	1.2396	0.5079	1.2396	1.1134
No log	46.0	184	1.2504	0.4754	1.2504	1.1182
No log	46.5	186	1.2758	0.4333	1.2758	1.1295
No log	47.0	188	1.2981	0.4034	1.2981	1.1393
No log	47.5	190	1.3028	0.4034	1.3028	1.1414
No log	48.0	192	1.2872	0.4034	1.2872	1.1345
No log	48.5	194	1.2626	0.4463	1.2626	1.1236
No log	49.0	196	1.2683	0.4426	1.2683	1.1262
No log	49.5	198	1.2920	0.4426	1.2920	1.1367
No log	50.0	200	1.3192	0.4463	1.3192	1.1486
No log	50.5	202	1.3620	0.4034	1.3620	1.1670
No log	51.0	204	1.4044	0.3667	1.4044	1.1851
No log	51.5	206	1.4226	0.3636	1.4226	1.1927
No log	52.0	208	1.4094	0.4034	1.4094	1.1872
No log	52.5	210	1.3759	0.4034	1.3759	1.1730
No log	53.0	212	1.3424	0.4034	1.3424	1.1586
No log	53.5	214	1.3354	0.3934	1.3354	1.1556
No log	54.0	216	1.3395	0.4228	1.3395	1.1574
No log	54.5	218	1.3115	0.4228	1.3115	1.1452
No log	55.0	220	1.2551	0.4228	1.2551	1.1203
No log	55.5	222	1.2348	0.5079	1.2348	1.1112
No log	56.0	224	1.2351	0.4724	1.2351	1.1113
No log	56.5	226	1.2351	0.4724	1.2351	1.1113
No log	57.0	228	1.2276	0.5079	1.2276	1.1080
No log	57.5	230	1.2182	0.5079	1.2182	1.1037
No log	58.0	232	1.2240	0.5197	1.2240	1.1064
No log	58.5	234	1.2413	0.5197	1.2413	1.1142
No log	59.0	236	1.2416	0.5197	1.2416	1.1143
No log	59.5	238	1.2423	0.5197	1.2423	1.1146
No log	60.0	240	1.2622	0.512	1.2622	1.1235
No log	60.5	242	1.2811	0.4298	1.2811	1.1318
No log	61.0	244	1.2853	0.4298	1.2853	1.1337
No log	61.5	246	1.2809	0.4426	1.2809	1.1318
No log	62.0	248	1.2795	0.5079	1.2795	1.1311
No log	62.5	250	1.2788	0.5079	1.2788	1.1308
No log	63.0	252	1.2693	0.5079	1.2693	1.1266
No log	63.5	254	1.2593	0.5	1.2593	1.1222
No log	64.0	256	1.2669	0.4715	1.2669	1.1256
No log	64.5	258	1.2750	0.4426	1.2750	1.1292
No log	65.0	260	1.2823	0.4426	1.2823	1.1324
No log	65.5	262	1.2858	0.4426	1.2858	1.1339
No log	66.0	264	1.2797	0.5	1.2797	1.1312
No log	66.5	266	1.2705	0.4715	1.2705	1.1272
No log	67.0	268	1.2680	0.4426	1.2680	1.1260
No log	67.5	270	1.2760	0.4333	1.2760	1.1296
No log	68.0	272	1.2854	0.4628	1.2854	1.1337
No log	68.5	274	1.2808	0.4333	1.2808	1.1317
No log	69.0	276	1.2762	0.4333	1.2762	1.1297
No log	69.5	278	1.2732	0.4426	1.2732	1.1283
No log	70.0	280	1.2929	0.48	1.2929	1.1371
No log	70.5	282	1.3142	0.4921	1.3142	1.1464
No log	71.0	284	1.3159	0.4516	1.3159	1.1471
No log	71.5	286	1.3215	0.4426	1.3215	1.1496
No log	72.0	288	1.3360	0.4034	1.3360	1.1559
No log	72.5	290	1.3571	0.4034	1.3571	1.1650
No log	73.0	292	1.3700	0.4034	1.3700	1.1705
No log	73.5	294	1.3711	0.4034	1.3711	1.1710
No log	74.0	296	1.3637	0.4034	1.3637	1.1678
No log	74.5	298	1.3490	0.4034	1.3490	1.1614
No log	75.0	300	1.3311	0.4167	1.3311	1.1538
No log	75.5	302	1.3109	0.4426	1.3109	1.1449
No log	76.0	304	1.2960	0.4426	1.2960	1.1384
No log	76.5	306	1.2841	0.4516	1.2841	1.1332
No log	77.0	308	1.2794	0.4516	1.2794	1.1311
No log	77.5	310	1.2750	0.4426	1.2750	1.1292
No log	78.0	312	1.2795	0.4132	1.2795	1.1311
No log	78.5	314	1.2843	0.4034	1.2843	1.1333
No log	79.0	316	1.2897	0.4034	1.2897	1.1357
No log	79.5	318	1.2893	0.4167	1.2893	1.1355
No log	80.0	320	1.2855	0.4426	1.2855	1.1338
No log	80.5	322	1.2891	0.4426	1.2891	1.1354
No log	81.0	324	1.2942	0.4426	1.2942	1.1376
No log	81.5	326	1.3008	0.4426	1.3008	1.1405
No log	82.0	328	1.3095	0.4426	1.3095	1.1443
No log	82.5	330	1.3146	0.4426	1.3146	1.1465
No log	83.0	332	1.3206	0.4426	1.3206	1.1492
No log	83.5	334	1.3252	0.4426	1.3252	1.1512
No log	84.0	336	1.3292	0.4553	1.3292	1.1529
No log	84.5	338	1.3314	0.4553	1.3314	1.1539
No log	85.0	340	1.3351	0.4426	1.3351	1.1555
No log	85.5	342	1.3310	0.4426	1.3310	1.1537
No log	86.0	344	1.3281	0.4426	1.3281	1.1524
No log	86.5	346	1.3261	0.4426	1.3261	1.1516
No log	87.0	348	1.3230	0.4426	1.3230	1.1502
No log	87.5	350	1.3205	0.4333	1.3205	1.1491
No log	88.0	352	1.3204	0.4333	1.3204	1.1491
No log	88.5	354	1.3201	0.4333	1.3201	1.1490
No log	89.0	356	1.3166	0.4333	1.3166	1.1474
No log	89.5	358	1.3148	0.4333	1.3148	1.1466
No log	90.0	360	1.3108	0.4333	1.3108	1.1449
No log	90.5	362	1.3076	0.4333	1.3076	1.1435
No log	91.0	364	1.3050	0.4333	1.3050	1.1424
No log	91.5	366	1.3019	0.4298	1.3019	1.1410
No log	92.0	368	1.3018	0.4333	1.3018	1.1410
No log	92.5	370	1.3033	0.4333	1.3033	1.1416
No log	93.0	372	1.3052	0.4333	1.3052	1.1425
No log	93.5	374	1.3060	0.4333	1.3060	1.1428
No log	94.0	376	1.3056	0.4333	1.3056	1.1426
No log	94.5	378	1.3047	0.4333	1.3047	1.1422
No log	95.0	380	1.3052	0.4333	1.3052	1.1424
No log	95.5	382	1.3050	0.4333	1.3050	1.1424
No log	96.0	384	1.3050	0.4333	1.3050	1.1423
No log	96.5	386	1.3051	0.4333	1.3051	1.1424
No log	97.0	388	1.3050	0.4333	1.3050	1.1423
No log	97.5	390	1.3053	0.4333	1.3053	1.1425
No log	98.0	392	1.3054	0.4333	1.3054	1.1426
No log	98.5	394	1.3050	0.4333	1.3050	1.1424
No log	99.0	396	1.3045	0.4333	1.3045	1.1421
No log	99.5	398	1.3041	0.4333	1.3041	1.1420
No log	100.0	400	1.3040	0.4333	1.3040	1.1419

Framework versions

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