ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k8_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: 0.6826
• Qwk: 0.7528
• Mse: 0.6826
• Rmse: 0.8262

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	0.0588	2	2.2058	0.0562	2.2058	1.4852
No log	0.1176	4	1.4472	0.1584	1.4472	1.2030
No log	0.1765	6	1.3207	0.1369	1.3207	1.1492
No log	0.2353	8	1.6241	0.3295	1.6241	1.2744
No log	0.2941	10	1.7928	0.2870	1.7928	1.3390
No log	0.3529	12	1.5302	0.3255	1.5302	1.2370
No log	0.4118	14	1.4913	0.3147	1.4913	1.2212
No log	0.4706	16	1.4633	0.3669	1.4633	1.2097
No log	0.5294	18	1.2813	0.2971	1.2813	1.1320
No log	0.5882	20	1.1271	0.3118	1.1271	1.0617
No log	0.6471	22	1.0649	0.3793	1.0649	1.0319
No log	0.7059	24	1.0182	0.4171	1.0182	1.0091
No log	0.7647	26	1.0313	0.4982	1.0313	1.0155
No log	0.8235	28	1.1599	0.5385	1.1599	1.0770
No log	0.8824	30	1.0092	0.5332	1.0092	1.0046
No log	0.9412	32	0.8973	0.4837	0.8973	0.9473
No log	1.0	34	0.9129	0.5309	0.9129	0.9555
No log	1.0588	36	0.9082	0.4978	0.9082	0.9530
No log	1.1176	38	0.9476	0.5069	0.9476	0.9735
No log	1.1765	40	1.0549	0.5435	1.0549	1.0271
No log	1.2353	42	0.9833	0.5451	0.9833	0.9916
No log	1.2941	44	0.8950	0.5348	0.8950	0.9460
No log	1.3529	46	0.9059	0.5793	0.9059	0.9518
No log	1.4118	48	0.9323	0.5879	0.9323	0.9656
No log	1.4706	50	0.8152	0.6228	0.8152	0.9029
No log	1.5294	52	0.8467	0.5576	0.8467	0.9202
No log	1.5882	54	0.8268	0.5622	0.8268	0.9093
No log	1.6471	56	0.8067	0.6044	0.8067	0.8982
No log	1.7059	58	1.2885	0.5363	1.2885	1.1351
No log	1.7647	60	1.7280	0.4884	1.7280	1.3145
No log	1.8235	62	1.5045	0.5189	1.5045	1.2266
No log	1.8824	64	1.0133	0.5451	1.0133	1.0066
No log	1.9412	66	0.8336	0.6195	0.8336	0.9130
No log	2.0	68	0.8201	0.5861	0.8201	0.9056
No log	2.0588	70	0.8480	0.6319	0.8480	0.9209
No log	2.1176	72	1.0745	0.5536	1.0745	1.0366
No log	2.1765	74	1.2662	0.5256	1.2662	1.1252
No log	2.2353	76	1.3533	0.5049	1.3533	1.1633
No log	2.2941	78	1.2067	0.5291	1.2067	1.0985
No log	2.3529	80	0.9653	0.5808	0.9653	0.9825
No log	2.4118	82	0.8603	0.5810	0.8603	0.9275
No log	2.4706	84	0.7931	0.6726	0.7931	0.8906
No log	2.5294	86	0.7734	0.6456	0.7734	0.8794
No log	2.5882	88	0.7429	0.6701	0.7429	0.8619
No log	2.6471	90	0.7552	0.6887	0.7552	0.8690
No log	2.7059	92	0.8324	0.7039	0.8324	0.9124
No log	2.7647	94	0.8236	0.7199	0.8236	0.9075
No log	2.8235	96	0.7568	0.6960	0.7568	0.8700
No log	2.8824	98	0.7159	0.7193	0.7159	0.8461
No log	2.9412	100	0.7525	0.7278	0.7525	0.8675
No log	3.0	102	0.9578	0.7031	0.9578	0.9787
No log	3.0588	104	1.0908	0.6673	1.0908	1.0444
No log	3.1176	106	0.9762	0.7113	0.9762	0.9880
No log	3.1765	108	0.7628	0.7376	0.7628	0.8734
No log	3.2353	110	0.6801	0.7040	0.6801	0.8247
No log	3.2941	112	0.6899	0.6947	0.6899	0.8306
No log	3.3529	114	0.6857	0.7040	0.6857	0.8281
No log	3.4118	116	0.7423	0.7057	0.7423	0.8616
No log	3.4706	118	0.8988	0.6353	0.8988	0.9481
No log	3.5294	120	0.9657	0.5917	0.9657	0.9827
No log	3.5882	122	0.9212	0.6147	0.9212	0.9598
No log	3.6471	124	0.8799	0.6147	0.8799	0.9380
No log	3.7059	126	0.8429	0.6296	0.8429	0.9181
No log	3.7647	128	0.9080	0.6194	0.9080	0.9529
No log	3.8235	130	0.9583	0.5872	0.9583	0.9789
No log	3.8824	132	0.9830	0.5632	0.9830	0.9915
No log	3.9412	134	0.9002	0.6254	0.9002	0.9488
No log	4.0	136	0.8109	0.7064	0.8109	0.9005
No log	4.0588	138	0.8067	0.7000	0.8067	0.8981
No log	4.1176	140	0.7496	0.6892	0.7496	0.8658
No log	4.1765	142	0.7503	0.7024	0.7503	0.8662
No log	4.2353	144	0.8098	0.6988	0.8098	0.8999
No log	4.2941	146	0.8901	0.6728	0.8901	0.9434
No log	4.3529	148	0.9004	0.6611	0.9004	0.9489
No log	4.4118	150	0.8209	0.6783	0.8209	0.9060
No log	4.4706	152	0.6983	0.7582	0.6983	0.8356
No log	4.5294	154	0.6747	0.7181	0.6747	0.8214
No log	4.5882	156	0.6712	0.7140	0.6712	0.8192
No log	4.6471	158	0.6817	0.7365	0.6817	0.8257
No log	4.7059	160	0.7057	0.7422	0.7057	0.8401
No log	4.7647	162	0.7324	0.7189	0.7324	0.8558
No log	4.8235	164	0.7440	0.7125	0.7440	0.8626
No log	4.8824	166	0.7033	0.7298	0.7033	0.8386
No log	4.9412	168	0.6736	0.7222	0.6736	0.8207
No log	5.0	170	0.6670	0.7351	0.6670	0.8167
No log	5.0588	172	0.6663	0.7471	0.6663	0.8163
No log	5.1176	174	0.6760	0.7471	0.6760	0.8222
No log	5.1765	176	0.6705	0.7471	0.6705	0.8189
No log	5.2353	178	0.6639	0.7448	0.6639	0.8148
No log	5.2941	180	0.6905	0.7512	0.6905	0.8309
No log	5.3529	182	0.7086	0.7448	0.7086	0.8418
No log	5.4118	184	0.7033	0.7448	0.7033	0.8386
No log	5.4706	186	0.7290	0.7337	0.7290	0.8538
No log	5.5294	188	0.7109	0.7509	0.7109	0.8431
No log	5.5882	190	0.6570	0.7527	0.6570	0.8106
No log	5.6471	192	0.6378	0.7336	0.6378	0.7986
No log	5.7059	194	0.6417	0.7516	0.6417	0.8011
No log	5.7647	196	0.6685	0.7458	0.6685	0.8176
No log	5.8235	198	0.7036	0.7226	0.7036	0.8388
No log	5.8824	200	0.7159	0.7372	0.7159	0.8461
No log	5.9412	202	0.7669	0.7209	0.7669	0.8757
No log	6.0	204	0.8543	0.6687	0.8543	0.9243
No log	6.0588	206	0.8542	0.6592	0.8542	0.9242
No log	6.1176	208	0.7848	0.7208	0.7848	0.8859
No log	6.1765	210	0.6956	0.7344	0.6956	0.8340
No log	6.2353	212	0.6668	0.7343	0.6668	0.8166
No log	6.2941	214	0.6523	0.7540	0.6523	0.8077
No log	6.3529	216	0.6455	0.7420	0.6455	0.8034
No log	6.4118	218	0.6488	0.7435	0.6488	0.8055
No log	6.4706	220	0.6783	0.7390	0.6783	0.8236
No log	6.5294	222	0.7184	0.7351	0.7184	0.8476
No log	6.5882	224	0.7321	0.7265	0.7321	0.8556
No log	6.6471	226	0.7268	0.7243	0.7268	0.8526
No log	6.7059	228	0.6923	0.7396	0.6923	0.8321
No log	6.7647	230	0.6652	0.7367	0.6652	0.8156
No log	6.8235	232	0.6695	0.7405	0.6695	0.8182
No log	6.8824	234	0.6702	0.7367	0.6702	0.8186
No log	6.9412	236	0.6738	0.7330	0.6738	0.8209
No log	7.0	238	0.6686	0.7337	0.6686	0.8177
No log	7.0588	240	0.6871	0.7285	0.6871	0.8289
No log	7.1176	242	0.6877	0.7254	0.6877	0.8293
No log	7.1765	244	0.6833	0.7424	0.6833	0.8266
No log	7.2353	246	0.6835	0.7424	0.6835	0.8268
No log	7.2941	248	0.6726	0.7431	0.6726	0.8201
No log	7.3529	250	0.6708	0.7431	0.6708	0.8190
No log	7.4118	252	0.6681	0.7431	0.6681	0.8174
No log	7.4706	254	0.6700	0.7450	0.6700	0.8185
No log	7.5294	256	0.6875	0.7366	0.6875	0.8292
No log	7.5882	258	0.7017	0.7241	0.7017	0.8377
No log	7.6471	260	0.7091	0.7219	0.7091	0.8421
No log	7.7059	262	0.7233	0.7336	0.7233	0.8505
No log	7.7647	264	0.7436	0.7350	0.7436	0.8623
No log	7.8235	266	0.7341	0.7371	0.7341	0.8568
No log	7.8824	268	0.7047	0.7278	0.7047	0.8395
No log	7.9412	270	0.6941	0.7444	0.6941	0.8331
No log	8.0	272	0.6927	0.7548	0.6927	0.8323
No log	8.0588	274	0.6882	0.7571	0.6882	0.8296
No log	8.1176	276	0.6867	0.7403	0.6867	0.8287
No log	8.1765	278	0.6902	0.7403	0.6902	0.8308
No log	8.2353	280	0.7071	0.7278	0.7071	0.8409
No log	8.2941	282	0.7313	0.7293	0.7313	0.8552
No log	8.3529	284	0.7465	0.7264	0.7465	0.8640
No log	8.4118	286	0.7556	0.7178	0.7556	0.8693
No log	8.4706	288	0.7459	0.7227	0.7459	0.8636
No log	8.5294	290	0.7242	0.7336	0.7242	0.8510
No log	8.5882	292	0.7056	0.7278	0.7056	0.8400
No log	8.6471	294	0.7016	0.7403	0.7016	0.8376
No log	8.7059	296	0.7042	0.7403	0.7042	0.8392
No log	8.7647	298	0.7164	0.7278	0.7164	0.8464
No log	8.8235	300	0.7226	0.7278	0.7226	0.8501
No log	8.8824	302	0.7347	0.7336	0.7347	0.8571
No log	8.9412	304	0.7508	0.7227	0.7508	0.8665
No log	9.0	306	0.7535	0.7126	0.7535	0.8680
No log	9.0588	308	0.7417	0.7293	0.7417	0.8612
No log	9.1176	310	0.7210	0.7278	0.7210	0.8491
No log	9.1765	312	0.7002	0.7278	0.7002	0.8368
No log	9.2353	314	0.6855	0.7424	0.6855	0.8280
No log	9.2941	316	0.6744	0.7470	0.6744	0.8212
No log	9.3529	318	0.6688	0.7476	0.6688	0.8178
No log	9.4118	320	0.6652	0.7439	0.6652	0.8156
No log	9.4706	322	0.6638	0.7401	0.6638	0.8148
No log	9.5294	324	0.6652	0.7439	0.6652	0.8156
No log	9.5882	326	0.6684	0.7476	0.6684	0.8176
No log	9.6471	328	0.6723	0.7514	0.6723	0.8199
No log	9.7059	330	0.6743	0.7571	0.6743	0.8212
No log	9.7647	332	0.6761	0.7528	0.6761	0.8223
No log	9.8235	334	0.6780	0.7528	0.6780	0.8234
No log	9.8824	336	0.6801	0.7528	0.6801	0.8247
No log	9.9412	338	0.6819	0.7528	0.6819	0.8258
No log	10.0	340	0.6826	0.7528	0.6826	0.8262

Framework versions

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