ArabicNewSplits5_FineTuningAraBERT_run3_AugV5_k5_task3_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: 0.7664
• Qwk: 0.2269
• Mse: 0.7664
• Rmse: 0.8755

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	0.0645	2	3.0743	0.0285	3.0743	1.7534
No log	0.1290	4	1.5493	-0.0070	1.5493	1.2447
No log	0.1935	6	1.9048	-0.0370	1.9048	1.3802
No log	0.2581	8	1.4233	-0.0327	1.4233	1.1930
No log	0.3226	10	1.2838	0.0	1.2838	1.1331
No log	0.3871	12	1.3289	0.0	1.3289	1.1528
No log	0.4516	14	1.4872	0.0	1.4872	1.2195
No log	0.5161	16	0.9857	0.0345	0.9857	0.9928
No log	0.5806	18	0.8396	0.0745	0.8396	0.9163
No log	0.6452	20	0.8487	0.0522	0.8487	0.9213
No log	0.7097	22	0.7906	0.0476	0.7906	0.8892
No log	0.7742	24	0.8202	0.0249	0.8202	0.9056
No log	0.8387	26	0.8094	0.0833	0.8094	0.8997
No log	0.9032	28	0.9209	0.0085	0.9209	0.9597
No log	0.9677	30	0.9140	-0.0041	0.9140	0.9560
No log	1.0323	32	0.9878	0.0159	0.9878	0.9939
No log	1.0968	34	1.1574	0.0038	1.1574	1.0758
No log	1.1613	36	1.1244	0.0038	1.1244	1.0604
No log	1.2258	38	1.1064	0.0	1.1064	1.0519
No log	1.2903	40	1.0030	0.1545	1.0030	1.0015
No log	1.3548	42	1.0718	0.0745	1.0718	1.0353
No log	1.4194	44	1.1306	0.0698	1.1306	1.0633
No log	1.4839	46	1.0317	0.0745	1.0317	1.0157
No log	1.5484	48	0.7355	0.0899	0.7355	0.8576
No log	1.6129	50	0.6088	0.0388	0.6088	0.7803
No log	1.6774	52	0.6019	0.0476	0.6019	0.7758
No log	1.7419	54	0.6392	-0.0256	0.6392	0.7995
No log	1.8065	56	0.7209	0.0968	0.7209	0.8491
No log	1.8710	58	0.9831	0.1416	0.9831	0.9915
No log	1.9355	60	1.0418	0.1525	1.0418	1.0207
No log	2.0	62	0.9210	0.1619	0.9210	0.9597
No log	2.0645	64	0.7111	0.0805	0.7111	0.8433
No log	2.1290	66	0.5999	0.0222	0.5999	0.7746
No log	2.1935	68	0.6055	-0.0303	0.6055	0.7782
No log	2.2581	70	0.6215	-0.0068	0.6215	0.7883
No log	2.3226	72	0.7403	0.1475	0.7403	0.8604
No log	2.3871	74	0.9457	0.1515	0.9457	0.9725
No log	2.4516	76	0.9224	0.1515	0.9224	0.9604
No log	2.5161	78	0.8728	0.1644	0.8728	0.9343
No log	2.5806	80	0.8968	0.1588	0.8968	0.9470
No log	2.6452	82	0.6493	0.2184	0.6493	0.8058
No log	2.7097	84	0.6471	0.1467	0.6471	0.8044
No log	2.7742	86	0.7006	0.1605	0.7006	0.8370
No log	2.8387	88	0.7788	0.2727	0.7788	0.8825
No log	2.9032	90	1.3370	0.1856	1.3370	1.1563
No log	2.9677	92	1.3900	0.1672	1.3900	1.1790
No log	3.0323	94	0.8071	0.2275	0.8071	0.8984
No log	3.0968	96	0.7060	0.2350	0.7060	0.8402
No log	3.1613	98	0.7714	0.1648	0.7714	0.8783
No log	3.2258	100	0.7199	0.0886	0.7199	0.8485
No log	3.2903	102	0.7676	0.0939	0.7676	0.8761
No log	3.3548	104	0.7926	0.1111	0.7926	0.8903
No log	3.4194	106	0.7433	0.0374	0.7433	0.8621
No log	3.4839	108	0.7104	0.2444	0.7104	0.8429
No log	3.5484	110	0.7029	0.2577	0.7029	0.8384
No log	3.6129	112	0.6793	0.3103	0.6793	0.8242
No log	3.6774	114	0.7459	0.1456	0.7459	0.8637
No log	3.7419	116	0.7008	0.1770	0.7008	0.8371
No log	3.8065	118	0.8249	0.1525	0.8249	0.9083
No log	3.8710	120	0.8242	0.1515	0.8242	0.9078
No log	3.9355	122	0.7126	0.2074	0.7126	0.8442
No log	4.0	124	0.7276	0.2074	0.7276	0.8530
No log	4.0645	126	0.6623	0.2986	0.6623	0.8138
No log	4.1290	128	0.6685	0.2986	0.6685	0.8176
No log	4.1935	130	0.6665	0.3422	0.6665	0.8164
No log	4.2581	132	0.7559	0.1351	0.7559	0.8694
No log	4.3226	134	1.1262	0.2171	1.1262	1.0612
No log	4.3871	136	1.0290	0.1877	1.0290	1.0144
No log	4.4516	138	0.7116	0.1644	0.7116	0.8436
No log	4.5161	140	0.6901	0.3208	0.6901	0.8307
No log	4.5806	142	0.8024	0.2000	0.8024	0.8958
No log	4.6452	144	1.0395	0.1587	1.0395	1.0196
No log	4.7097	146	1.0765	0.2448	1.0765	1.0376
No log	4.7742	148	1.0529	0.2171	1.0529	1.0261
No log	4.8387	150	0.8983	0.1628	0.8983	0.9478
No log	4.9032	152	0.8309	0.3527	0.8309	0.9116
No log	4.9677	154	0.7977	0.3527	0.7977	0.8931
No log	5.0323	156	0.7813	0.2405	0.7813	0.8839
No log	5.0968	158	1.0559	0.2456	1.0559	1.0276
No log	5.1613	160	1.0036	0.2456	1.0036	1.0018
No log	5.2258	162	0.7591	0.3702	0.7591	0.8713
No log	5.2903	164	0.6244	0.3488	0.6244	0.7902
No log	5.3548	166	0.6114	0.3333	0.6114	0.7819
No log	5.4194	168	0.6352	0.3035	0.6352	0.7970
No log	5.4839	170	0.6783	0.2390	0.6783	0.8236
No log	5.5484	172	0.6969	0.2986	0.6969	0.8348
No log	5.6129	174	0.7546	0.2000	0.7546	0.8687
No log	5.6774	176	0.7644	0.2140	0.7644	0.8743
No log	5.7419	178	0.7749	0.2681	0.7749	0.8803
No log	5.8065	180	0.9106	0.1429	0.9106	0.9543
No log	5.8710	182	1.1567	0.1096	1.1567	1.0755
No log	5.9355	184	1.0940	0.1340	1.0940	1.0460
No log	6.0	186	0.9892	0.0861	0.9892	0.9946
No log	6.0645	188	1.0413	0.1601	1.0413	1.0205
No log	6.1290	190	0.9410	0.1545	0.9410	0.9701
No log	6.1935	192	0.8884	0.2863	0.8884	0.9426
No log	6.2581	194	0.8806	0.2698	0.8806	0.9384
No log	6.3226	196	0.9159	0.1588	0.9159	0.9570
No log	6.3871	198	1.2242	0.1125	1.2242	1.1065
No log	6.4516	200	1.3622	0.0692	1.3622	1.1672
No log	6.5161	202	1.2152	0.0927	1.2152	1.1024
No log	6.5806	204	0.8948	0.1746	0.8948	0.9459
No log	6.6452	206	0.7296	0.2511	0.7296	0.8542
No log	6.7097	208	0.7068	0.2793	0.7068	0.8407
No log	6.7742	210	0.7656	0.2300	0.7656	0.8750
No log	6.8387	212	0.8876	0.2199	0.8876	0.9421
No log	6.9032	214	0.9621	0.1882	0.9621	0.9809
No log	6.9677	216	0.8828	0.2195	0.8828	0.9396
No log	7.0323	218	0.7039	0.2300	0.7039	0.8390
No log	7.0968	220	0.6435	0.3267	0.6435	0.8022
No log	7.1613	222	0.6325	0.3684	0.6325	0.7953
No log	7.2258	224	0.6352	0.3299	0.6352	0.7970
No log	7.2903	226	0.6842	0.2900	0.6842	0.8272
No log	7.3548	228	0.6731	0.3303	0.6731	0.8204
No log	7.4194	230	0.6358	0.3061	0.6358	0.7974
No log	7.4839	232	0.6611	0.3274	0.6611	0.8131
No log	7.5484	234	0.6859	0.2711	0.6859	0.8282
No log	7.6129	236	0.6918	0.2711	0.6918	0.8318
No log	7.6774	238	0.7152	0.2711	0.7152	0.8457
No log	7.7419	240	0.7619	0.3214	0.7619	0.8729
No log	7.8065	242	0.8349	0.2195	0.8349	0.9137
No log	7.8710	244	0.8541	0.25	0.8541	0.9242
No log	7.9355	246	0.7720	0.25	0.7720	0.8786
No log	8.0	248	0.7596	0.2423	0.7596	0.8716
No log	8.0645	250	0.7903	0.2397	0.7903	0.8890
No log	8.1290	252	0.7613	0.2605	0.7613	0.8725
No log	8.1935	254	0.7156	0.3138	0.7156	0.8460
No log	8.2581	256	0.7077	0.3138	0.7077	0.8412
No log	8.3226	258	0.7066	0.3138	0.7066	0.8406
No log	8.3871	260	0.7483	0.2333	0.7483	0.8650
No log	8.4516	262	0.8616	0.2727	0.8616	0.9282
No log	8.5161	264	0.9930	0.2448	0.9930	0.9965
No log	8.5806	266	0.9957	0.2448	0.9957	0.9978
No log	8.6452	268	0.9486	0.2768	0.9486	0.9740
No log	8.7097	270	0.8606	0.2727	0.8606	0.9277
No log	8.7742	272	0.8016	0.2771	0.8016	0.8953
No log	8.8387	274	0.7622	0.2713	0.7622	0.8730
No log	8.9032	276	0.7608	0.2713	0.7608	0.8722
No log	8.9677	278	0.7212	0.2711	0.7212	0.8492
No log	9.0323	280	0.7130	0.2711	0.7130	0.8444
No log	9.0968	282	0.7162	0.2711	0.7162	0.8463
No log	9.1613	284	0.7218	0.2696	0.7218	0.8496
No log	9.2258	286	0.7333	0.2696	0.7333	0.8564
No log	9.2903	288	0.7244	0.2618	0.7244	0.8511
No log	9.3548	290	0.7319	0.2618	0.7319	0.8555
No log	9.4194	292	0.7401	0.2618	0.7401	0.8603
No log	9.4839	294	0.7427	0.2618	0.7427	0.8618
No log	9.5484	296	0.7532	0.2618	0.7532	0.8679
No log	9.6129	298	0.7646	0.2269	0.7646	0.8744
No log	9.6774	300	0.7752	0.2333	0.7752	0.8805
No log	9.7419	302	0.7755	0.2263	0.7755	0.8806
No log	9.8065	304	0.7703	0.2269	0.7703	0.8776
No log	9.8710	306	0.7664	0.2269	0.7664	0.8755
No log	9.9355	308	0.7666	0.2269	0.7666	0.8756
No log	10.0	310	0.7664	0.2269	0.7664	0.8755

Framework versions

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