ArabicNewSplits7_FineTuningAraBERT_noAug_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: 0.6749
• Qwk: 0.7448
• Mse: 0.6749
• Rmse: 0.8215

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	5.7283	0.0	5.7283	2.3934
No log	1.0	4	4.4212	0.0899	4.4212	2.1027
No log	1.5	6	2.8327	0.1091	2.8327	1.6831
No log	2.0	8	2.0037	0.1818	2.0037	1.4155
No log	2.5	10	1.5763	0.1143	1.5763	1.2555
No log	3.0	12	1.7950	0.1345	1.7950	1.3398
No log	3.5	14	1.7567	0.2439	1.7567	1.3254
No log	4.0	16	1.3368	0.4640	1.3368	1.1562
No log	4.5	18	1.1361	0.5625	1.1361	1.0659
No log	5.0	20	1.0035	0.6	1.0035	1.0018
No log	5.5	22	0.7957	0.6466	0.7957	0.8920
No log	6.0	24	0.9489	0.6803	0.9489	0.9741
No log	6.5	26	0.9905	0.6711	0.9905	0.9952
No log	7.0	28	0.7061	0.7215	0.7061	0.8403
No log	7.5	30	0.7623	0.7089	0.7623	0.8731
No log	8.0	32	0.7881	0.675	0.7881	0.8877
No log	8.5	34	0.7602	0.7286	0.7602	0.8719
No log	9.0	36	0.7555	0.7324	0.7555	0.8692
No log	9.5	38	0.7334	0.7671	0.7334	0.8564
No log	10.0	40	0.8464	0.6901	0.8464	0.9200
No log	10.5	42	0.7635	0.7093	0.7635	0.8738
No log	11.0	44	0.6611	0.7875	0.6611	0.8131
No log	11.5	46	0.6986	0.7531	0.6986	0.8358
No log	12.0	48	0.6103	0.8090	0.6103	0.7812
No log	12.5	50	0.9149	0.7374	0.9149	0.9565
No log	13.0	52	0.8405	0.7423	0.8405	0.9168
No log	13.5	54	0.6384	0.7771	0.6384	0.7990
No log	14.0	56	0.6231	0.7712	0.6231	0.7894
No log	14.5	58	0.7146	0.7568	0.7146	0.8453
No log	15.0	60	0.8190	0.6849	0.8190	0.9050
No log	15.5	62	0.7697	0.7222	0.7697	0.8773
No log	16.0	64	0.7883	0.7260	0.7883	0.8879
No log	16.5	66	0.7168	0.6993	0.7168	0.8467
No log	17.0	68	0.6648	0.7467	0.6648	0.8153
No log	17.5	70	0.6308	0.7550	0.6308	0.7943
No log	18.0	72	0.6351	0.775	0.6351	0.7969
No log	18.5	74	0.6116	0.7799	0.6116	0.7821
No log	19.0	76	0.5927	0.7564	0.5927	0.7699
No log	19.5	78	0.6433	0.7799	0.6433	0.8020
No log	20.0	80	0.6251	0.7613	0.6251	0.7907
No log	20.5	82	0.6753	0.7901	0.6753	0.8218
No log	21.0	84	0.6971	0.7901	0.6971	0.8349
No log	21.5	86	0.5967	0.7632	0.5967	0.7725
No log	22.0	88	0.6512	0.7595	0.6512	0.8069
No log	22.5	90	0.8192	0.6792	0.8192	0.9051
No log	23.0	92	0.7403	0.7215	0.7403	0.8604
No log	23.5	94	0.5969	0.7763	0.5969	0.7726
No log	24.0	96	0.7296	0.7632	0.7296	0.8542
No log	24.5	98	0.7538	0.7206	0.7538	0.8682
No log	25.0	100	0.7907	0.6718	0.7907	0.8892
No log	25.5	102	0.7714	0.6866	0.7714	0.8783
No log	26.0	104	0.7152	0.7101	0.7152	0.8457
No log	26.5	106	0.6623	0.7183	0.6623	0.8138
No log	27.0	108	0.6467	0.7361	0.6467	0.8042
No log	27.5	110	0.6404	0.8	0.6404	0.8002
No log	28.0	112	0.6807	0.7347	0.6807	0.8251
No log	28.5	114	0.6866	0.7347	0.6866	0.8286
No log	29.0	116	0.6683	0.7397	0.6683	0.8175
No log	29.5	118	0.7229	0.75	0.7229	0.8503
No log	30.0	120	0.7675	0.72	0.7675	0.8761
No log	30.5	122	0.7178	0.7101	0.7178	0.8472
No log	31.0	124	0.7037	0.6866	0.7037	0.8389
No log	31.5	126	0.6864	0.7234	0.6864	0.8285
No log	32.0	128	0.6806	0.7234	0.6806	0.8250
No log	32.5	130	0.6529	0.7785	0.6529	0.8081
No log	33.0	132	0.6303	0.7815	0.6303	0.7939
No log	33.5	134	0.6330	0.7785	0.6330	0.7956
No log	34.0	136	0.6680	0.7871	0.6680	0.8173
No log	34.5	138	0.6989	0.7976	0.6989	0.8360
No log	35.0	140	0.6774	0.8049	0.6774	0.8231
No log	35.5	142	0.6164	0.7898	0.6164	0.7851
No log	36.0	144	0.6464	0.7898	0.6464	0.8040
No log	36.5	146	0.7079	0.7975	0.7079	0.8414
No log	37.0	148	0.7986	0.7673	0.7986	0.8936
No log	37.5	150	0.7841	0.7673	0.7841	0.8855
No log	38.0	152	0.7336	0.7550	0.7336	0.8565
No log	38.5	154	0.6689	0.7361	0.6689	0.8178
No log	39.0	156	0.6495	0.7333	0.6495	0.8059
No log	39.5	158	0.6309	0.7333	0.6309	0.7943
No log	40.0	160	0.6394	0.7643	0.6394	0.7996
No log	40.5	162	0.6691	0.7643	0.6691	0.8180
No log	41.0	164	0.6491	0.7532	0.6491	0.8057
No log	41.5	166	0.6487	0.7799	0.6487	0.8054
No log	42.0	168	0.6488	0.775	0.6488	0.8055
No log	42.5	170	0.6648	0.7436	0.6648	0.8153
No log	43.0	172	0.7060	0.7564	0.7060	0.8403
No log	43.5	174	0.7596	0.7531	0.7595	0.8715
No log	44.0	176	0.7547	0.7564	0.7547	0.8687
No log	44.5	178	0.7462	0.6993	0.7462	0.8638
No log	45.0	180	0.7579	0.7042	0.7579	0.8706
No log	45.5	182	0.7430	0.7133	0.7430	0.8620
No log	46.0	184	0.7356	0.7133	0.7356	0.8577
No log	46.5	186	0.7246	0.7133	0.7246	0.8512
No log	47.0	188	0.7530	0.7403	0.7530	0.8678
No log	47.5	190	0.8012	0.7636	0.8012	0.8951
No log	48.0	192	0.7931	0.7738	0.7931	0.8906
No log	48.5	194	0.7278	0.7702	0.7278	0.8531
No log	49.0	196	0.6743	0.7483	0.6743	0.8211
No log	49.5	198	0.6482	0.7448	0.6482	0.8051
No log	50.0	200	0.6446	0.7397	0.6446	0.8029
No log	50.5	202	0.6448	0.7310	0.6448	0.8030
No log	51.0	204	0.6260	0.7361	0.6260	0.7912
No log	51.5	206	0.6310	0.7234	0.6310	0.7944
No log	52.0	208	0.6484	0.7448	0.6484	0.8052
No log	52.5	210	0.6807	0.7234	0.6807	0.8251
No log	53.0	212	0.6967	0.7347	0.6967	0.8347
No log	53.5	214	0.7160	0.7682	0.7160	0.8462
No log	54.0	216	0.7614	0.7578	0.7614	0.8726
No log	54.5	218	0.7615	0.7578	0.7615	0.8726
No log	55.0	220	0.7213	0.7595	0.7213	0.8493
No log	55.5	222	0.7117	0.7578	0.7117	0.8436
No log	56.0	224	0.6695	0.7421	0.6695	0.8182
No log	56.5	226	0.6704	0.7407	0.6704	0.8188
No log	57.0	228	0.7212	0.7857	0.7212	0.8492
No log	57.5	230	0.7341	0.7758	0.7341	0.8568
No log	58.0	232	0.7238	0.7831	0.7238	0.8508
No log	58.5	234	0.7268	0.7758	0.7268	0.8525
No log	59.0	236	0.7271	0.7578	0.7271	0.8527
No log	59.5	238	0.6985	0.75	0.6985	0.8357
No log	60.0	240	0.6931	0.7234	0.6931	0.8325
No log	60.5	242	0.7165	0.7	0.7165	0.8465
No log	61.0	244	0.7219	0.7234	0.7219	0.8496
No log	61.5	246	0.7521	0.7092	0.7521	0.8672
No log	62.0	248	0.7855	0.75	0.7855	0.8863
No log	62.5	250	0.7865	0.7484	0.7865	0.8868
No log	63.0	252	0.7517	0.75	0.7517	0.8670
No log	63.5	254	0.7019	0.75	0.7019	0.8378
No log	64.0	256	0.7025	0.7484	0.7025	0.8381
No log	64.5	258	0.7140	0.7613	0.7140	0.8450
No log	65.0	260	0.7186	0.7403	0.7186	0.8477
No log	65.5	262	0.7214	0.7613	0.7214	0.8493
No log	66.0	264	0.7213	0.7595	0.7213	0.8493
No log	66.5	266	0.6882	0.7403	0.6882	0.8296
No log	67.0	268	0.6727	0.7417	0.6727	0.8202
No log	67.5	270	0.6825	0.7467	0.6825	0.8262
No log	68.0	272	0.6921	0.7222	0.6921	0.8319
No log	68.5	274	0.7065	0.7234	0.7065	0.8405
No log	69.0	276	0.7205	0.7101	0.7205	0.8488
No log	69.5	278	0.7308	0.7101	0.7308	0.8549
No log	70.0	280	0.7660	0.7083	0.7660	0.8752
No log	70.5	282	0.7801	0.7172	0.7801	0.8832
No log	71.0	284	0.7736	0.7172	0.7736	0.8795
No log	71.5	286	0.7469	0.7083	0.7469	0.8642
No log	72.0	288	0.7196	0.7101	0.7196	0.8483
No log	72.5	290	0.7104	0.7101	0.7104	0.8428
No log	73.0	292	0.6989	0.7361	0.6989	0.8360
No log	73.5	294	0.6817	0.7361	0.6817	0.8256
No log	74.0	296	0.6807	0.7361	0.6807	0.8250
No log	74.5	298	0.6898	0.7297	0.6898	0.8306
No log	75.0	300	0.7230	0.76	0.7230	0.8503
No log	75.5	302	0.7631	0.7284	0.7631	0.8735
No log	76.0	304	0.7765	0.7284	0.7765	0.8812
No log	76.5	306	0.7481	0.75	0.7481	0.8649
No log	77.0	308	0.7310	0.7848	0.7310	0.8550
No log	77.5	310	0.7070	0.76	0.7070	0.8408
No log	78.0	312	0.6705	0.7361	0.6705	0.8188
No log	78.5	314	0.6472	0.7361	0.6472	0.8045
No log	79.0	316	0.6447	0.7361	0.6447	0.8029
No log	79.5	318	0.6460	0.7347	0.6460	0.8037
No log	80.0	320	0.6673	0.7763	0.6673	0.8169
No log	80.5	322	0.6800	0.7975	0.6800	0.8246
No log	81.0	324	0.6779	0.7871	0.6779	0.8233
No log	81.5	326	0.6616	0.7651	0.6616	0.8134
No log	82.0	328	0.6539	0.7671	0.6539	0.8086
No log	82.5	330	0.6553	0.7763	0.6553	0.8095
No log	83.0	332	0.6531	0.7763	0.6531	0.8081
No log	83.5	334	0.6594	0.7671	0.6594	0.8121
No log	84.0	336	0.6597	0.7671	0.6597	0.8122
No log	84.5	338	0.6486	0.7671	0.6486	0.8054
No log	85.0	340	0.6342	0.7483	0.6342	0.7964
No log	85.5	342	0.6275	0.7432	0.6275	0.7922
No log	86.0	344	0.6329	0.7310	0.6329	0.7955
No log	86.5	346	0.6419	0.7586	0.6419	0.8012
No log	87.0	348	0.6416	0.7361	0.6416	0.8010
No log	87.5	350	0.6460	0.7361	0.6460	0.8038
No log	88.0	352	0.6464	0.7361	0.6464	0.8040
No log	88.5	354	0.6448	0.7310	0.6448	0.8030
No log	89.0	356	0.6464	0.7183	0.6464	0.8040
No log	89.5	358	0.6528	0.7183	0.6528	0.8080
No log	90.0	360	0.6637	0.7183	0.6637	0.8147
No log	90.5	362	0.6732	0.7183	0.6732	0.8205
No log	91.0	364	0.6781	0.7234	0.6781	0.8235
No log	91.5	366	0.6850	0.7234	0.6850	0.8277
No log	92.0	368	0.6902	0.7448	0.6902	0.8308
No log	92.5	370	0.6941	0.7448	0.6941	0.8331
No log	93.0	372	0.6951	0.7361	0.6951	0.8337
No log	93.5	374	0.6946	0.7361	0.6946	0.8334
No log	94.0	376	0.6924	0.7361	0.6924	0.8321
No log	94.5	378	0.6860	0.7448	0.6860	0.8283
No log	95.0	380	0.6789	0.7448	0.6789	0.8240
No log	95.5	382	0.6743	0.7448	0.6743	0.8211
No log	96.0	384	0.6730	0.7448	0.6730	0.8204
No log	96.5	386	0.6732	0.7448	0.6732	0.8205
No log	97.0	388	0.6743	0.7448	0.6743	0.8212
No log	97.5	390	0.6755	0.7448	0.6755	0.8219
No log	98.0	392	0.6755	0.7448	0.6755	0.8219
No log	98.5	394	0.6746	0.7448	0.6746	0.8213
No log	99.0	396	0.6743	0.7448	0.6743	0.8212
No log	99.5	398	0.6747	0.7448	0.6747	0.8214
No log	100.0	400	0.6749	0.7448	0.6749	0.8215

Framework versions

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