ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run3_AugV5_k5_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: 0.6389
• Qwk: 0.7568
• Mse: 0.6389
• Rmse: 0.7993

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	0.0667	2	5.2467	-0.0057	5.2467	2.2906
No log	0.1333	4	3.3484	0.0650	3.3484	1.8299
No log	0.2	6	2.0101	0.1162	2.0101	1.4178
No log	0.2667	8	1.3767	0.1236	1.3767	1.1733
No log	0.3333	10	1.1681	0.3386	1.1681	1.0808
No log	0.4	12	1.1517	0.3408	1.1517	1.0732
No log	0.4667	14	1.0905	0.3666	1.0905	1.0443
No log	0.5333	16	1.0190	0.2691	1.0190	1.0095
No log	0.6	18	0.9952	0.3869	0.9952	0.9976
No log	0.6667	20	0.9261	0.3753	0.9261	0.9623
No log	0.7333	22	0.8921	0.4251	0.8921	0.9445
No log	0.8	24	0.8159	0.4996	0.8159	0.9033
No log	0.8667	26	0.8145	0.5686	0.8145	0.9025
No log	0.9333	28	1.0542	0.4506	1.0542	1.0268
No log	1.0	30	1.0613	0.5146	1.0613	1.0302
No log	1.0667	32	0.7882	0.6375	0.7882	0.8878
No log	1.1333	34	0.6697	0.7026	0.6697	0.8183
No log	1.2	36	0.6011	0.7176	0.6011	0.7753
No log	1.2667	38	0.6049	0.7314	0.6049	0.7778
No log	1.3333	40	0.9806	0.5633	0.9806	0.9903
No log	1.4	42	1.6824	0.3648	1.6824	1.2971
No log	1.4667	44	1.9689	0.2733	1.9689	1.4032
No log	1.5333	46	1.4227	0.4463	1.4227	1.1928
No log	1.6	48	0.7443	0.6790	0.7443	0.8627
No log	1.6667	50	0.5737	0.75	0.5737	0.7574
No log	1.7333	52	0.6184	0.7312	0.6184	0.7864
No log	1.8	54	0.7143	0.7211	0.7143	0.8452
No log	1.8667	56	0.7128	0.7001	0.7128	0.8443
No log	1.9333	58	0.6839	0.7205	0.6839	0.8270
No log	2.0	60	0.6313	0.7306	0.6313	0.7945
No log	2.0667	62	0.5875	0.7611	0.5875	0.7665
No log	2.1333	64	0.5943	0.7254	0.5943	0.7709
No log	2.2	66	0.6015	0.7323	0.6015	0.7756
No log	2.2667	68	0.5715	0.7386	0.5715	0.7560
No log	2.3333	70	0.6667	0.7131	0.6667	0.8165
No log	2.4	72	0.7040	0.7052	0.7040	0.8390
No log	2.4667	74	0.5849	0.7398	0.5849	0.7648
No log	2.5333	76	0.5672	0.7523	0.5672	0.7531
No log	2.6	78	0.5584	0.7629	0.5584	0.7473
No log	2.6667	80	0.5634	0.7473	0.5634	0.7506
No log	2.7333	82	0.5944	0.7472	0.5944	0.7710
No log	2.8	84	0.6561	0.7205	0.6561	0.8100
No log	2.8667	86	0.6418	0.7220	0.6418	0.8011
No log	2.9333	88	0.6258	0.7355	0.6258	0.7911
No log	3.0	90	0.5660	0.7728	0.5660	0.7523
No log	3.0667	92	0.6394	0.7527	0.6394	0.7996
No log	3.1333	94	0.5925	0.7569	0.5925	0.7697
No log	3.2	96	0.5653	0.7659	0.5653	0.7519
No log	3.2667	98	0.5774	0.7431	0.5774	0.7599
No log	3.3333	100	0.5705	0.7668	0.5705	0.7553
No log	3.4	102	0.5990	0.7683	0.5990	0.7740
No log	3.4667	104	0.6053	0.7625	0.6053	0.7780
No log	3.5333	106	0.6064	0.7562	0.6064	0.7787
No log	3.6	108	0.5934	0.7729	0.5934	0.7703
No log	3.6667	110	0.6010	0.7622	0.6010	0.7753
No log	3.7333	112	0.6043	0.7656	0.6043	0.7774
No log	3.8	114	0.5950	0.7754	0.5950	0.7714
No log	3.8667	116	0.6002	0.7705	0.6002	0.7747
No log	3.9333	118	0.5891	0.7546	0.5891	0.7675
No log	4.0	120	0.6131	0.7300	0.6131	0.7830
No log	4.0667	122	0.6530	0.6912	0.6530	0.8081
No log	4.1333	124	0.5811	0.7274	0.5811	0.7623
No log	4.2	126	0.5698	0.7695	0.5698	0.7549
No log	4.2667	128	0.6027	0.7613	0.6027	0.7763
No log	4.3333	130	0.6107	0.7503	0.6107	0.7815
No log	4.4	132	0.6088	0.7737	0.6088	0.7802
No log	4.4667	134	0.6383	0.7705	0.6383	0.7989
No log	4.5333	136	0.6821	0.7567	0.6821	0.8259
No log	4.6	138	0.6911	0.7411	0.6911	0.8313
No log	4.6667	140	0.6875	0.7573	0.6875	0.8291
No log	4.7333	142	0.6685	0.7578	0.6685	0.8176
No log	4.8	144	0.6564	0.7561	0.6564	0.8102
No log	4.8667	146	0.6889	0.7304	0.6889	0.8300
No log	4.9333	148	0.7857	0.7145	0.7857	0.8864
No log	5.0	150	0.7321	0.7092	0.7321	0.8556
No log	5.0667	152	0.6189	0.7656	0.6189	0.7867
No log	5.1333	154	0.6383	0.7504	0.6383	0.7989
No log	5.2	156	0.6938	0.7222	0.6938	0.8329
No log	5.2667	158	0.6476	0.7329	0.6476	0.8047
No log	5.3333	160	0.6050	0.7441	0.6050	0.7778
No log	5.4	162	0.5981	0.7504	0.5981	0.7734
No log	5.4667	164	0.6135	0.7822	0.6135	0.7833
No log	5.5333	166	0.6051	0.7730	0.6051	0.7779
No log	5.6	168	0.6123	0.7367	0.6123	0.7825
No log	5.6667	170	0.6324	0.7422	0.6324	0.7953
No log	5.7333	172	0.6480	0.7247	0.6480	0.8050
No log	5.8	174	0.6154	0.7274	0.6154	0.7845
No log	5.8667	176	0.6136	0.7557	0.6136	0.7833
No log	5.9333	178	0.6254	0.7625	0.6254	0.7908
No log	6.0	180	0.6509	0.7250	0.6509	0.8068
No log	6.0667	182	0.7110	0.7162	0.7110	0.8432
No log	6.1333	184	0.7202	0.7137	0.7202	0.8486
No log	6.2	186	0.6600	0.7174	0.6600	0.8124
No log	6.2667	188	0.6444	0.7210	0.6444	0.8027
No log	6.3333	190	0.6470	0.7194	0.6470	0.8044
No log	6.4	192	0.6607	0.7156	0.6607	0.8128
No log	6.4667	194	0.7227	0.7102	0.7227	0.8501
No log	6.5333	196	0.7110	0.6948	0.7110	0.8432
No log	6.6	198	0.6420	0.7450	0.6420	0.8013
No log	6.6667	200	0.6260	0.7510	0.6260	0.7912
No log	6.7333	202	0.6253	0.7446	0.6253	0.7907
No log	6.8	204	0.6319	0.7436	0.6319	0.7949
No log	6.8667	206	0.6401	0.7436	0.6401	0.8000
No log	6.9333	208	0.6443	0.7396	0.6443	0.8027
No log	7.0	210	0.6468	0.7388	0.6468	0.8042
No log	7.0667	212	0.6443	0.7359	0.6443	0.8027
No log	7.1333	214	0.6429	0.7354	0.6429	0.8018
No log	7.2	216	0.6549	0.7097	0.6549	0.8093
No log	7.2667	218	0.6738	0.7023	0.6738	0.8208
No log	7.3333	220	0.6553	0.7087	0.6553	0.8095
No log	7.4	222	0.6384	0.7389	0.6384	0.7990
No log	7.4667	224	0.6342	0.7437	0.6342	0.7963
No log	7.5333	226	0.6350	0.7370	0.6350	0.7968
No log	7.6	228	0.6421	0.7238	0.6421	0.8013
No log	7.6667	230	0.6581	0.7369	0.6581	0.8113
No log	7.7333	232	0.6657	0.7363	0.6657	0.8159
No log	7.8	234	0.6983	0.7032	0.6983	0.8357
No log	7.8667	236	0.7008	0.7027	0.7008	0.8371
No log	7.9333	238	0.6760	0.7329	0.6760	0.8222
No log	8.0	240	0.6538	0.7421	0.6538	0.8086
No log	8.0667	242	0.6399	0.7462	0.6399	0.8000
No log	8.1333	244	0.6358	0.7464	0.6358	0.7974
No log	8.2	246	0.6411	0.7423	0.6411	0.8007
No log	8.2667	248	0.6290	0.7548	0.6290	0.7931
No log	8.3333	250	0.6219	0.7563	0.6219	0.7886
No log	8.4	252	0.6204	0.7688	0.6204	0.7877
No log	8.4667	254	0.6254	0.7563	0.6254	0.7908
No log	8.5333	256	0.6332	0.7515	0.6332	0.7957
No log	8.6	258	0.6564	0.7542	0.6564	0.8102
No log	8.6667	260	0.6780	0.7181	0.6780	0.8234
No log	8.7333	262	0.6765	0.7179	0.6765	0.8225
No log	8.8	264	0.6625	0.7162	0.6625	0.8139
No log	8.8667	266	0.6412	0.7597	0.6412	0.8007
No log	8.9333	268	0.6296	0.7572	0.6296	0.7935
No log	9.0	270	0.6227	0.7719	0.6227	0.7891
No log	9.0667	272	0.6216	0.7753	0.6216	0.7884
No log	9.1333	274	0.6265	0.7644	0.6265	0.7915
No log	9.2	276	0.6327	0.7536	0.6327	0.7955
No log	9.2667	278	0.6378	0.7536	0.6378	0.7986
No log	9.3333	280	0.6407	0.7572	0.6407	0.8005
No log	9.4	282	0.6405	0.7622	0.6405	0.8003
No log	9.4667	284	0.6391	0.7613	0.6391	0.7994
No log	9.5333	286	0.6384	0.7705	0.6384	0.7990
No log	9.6	288	0.6378	0.7678	0.6378	0.7987
No log	9.6667	290	0.6381	0.7539	0.6381	0.7988
No log	9.7333	292	0.6374	0.7573	0.6374	0.7983
No log	9.8	294	0.6376	0.7534	0.6376	0.7985
No log	9.8667	296	0.6383	0.7568	0.6383	0.7989
No log	9.9333	298	0.6389	0.7568	0.6389	0.7993
No log	10.0	300	0.6389	0.7568	0.6389	0.7993

Framework versions

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