ArabicNewSplits6_WithDuplicationsForScore5_FineTuningAraBERT_run2_AugV5_k4_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: 0.8731
• Qwk: 0.6627
• Mse: 0.8731
• Rmse: 0.9344

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	0.0769	2	4.9830	-0.0009	4.9830	2.2323
No log	0.1538	4	2.9812	0.0802	2.9812	1.7266
No log	0.2308	6	1.6770	0.1187	1.6770	1.2950
No log	0.3077	8	1.3169	0.2519	1.3169	1.1476
No log	0.3846	10	1.3257	0.2226	1.3257	1.1514
No log	0.4615	12	1.1761	0.2168	1.1761	1.0845
No log	0.5385	14	1.1329	0.1947	1.1329	1.0644
No log	0.6154	16	1.1274	0.1814	1.1274	1.0618
No log	0.6923	18	1.1469	0.1681	1.1469	1.0710
No log	0.7692	20	1.1763	0.1218	1.1763	1.0846
No log	0.8462	22	1.1639	0.1218	1.1639	1.0788
No log	0.9231	24	1.0680	0.1947	1.0680	1.0334
No log	1.0	26	1.0902	0.3729	1.0902	1.0442
No log	1.0769	28	1.8380	0.0679	1.8380	1.3557
No log	1.1538	30	2.4054	0.0454	2.4054	1.5509
No log	1.2308	32	2.0091	0.1093	2.0091	1.4174
No log	1.3077	34	1.2600	0.1522	1.2600	1.1225
No log	1.3846	36	0.9010	0.4650	0.9010	0.9492
No log	1.4615	38	0.8627	0.4511	0.8627	0.9288
No log	1.5385	40	0.8715	0.5013	0.8715	0.9335
No log	1.6154	42	0.8455	0.4667	0.8455	0.9195
No log	1.6923	44	0.8318	0.4714	0.8318	0.9120
No log	1.7692	46	0.8059	0.4844	0.8059	0.8977
No log	1.8462	48	0.7754	0.5745	0.7754	0.8806
No log	1.9231	50	0.7490	0.5918	0.7490	0.8655
No log	2.0	52	0.7146	0.5834	0.7146	0.8453
No log	2.0769	54	0.7102	0.5975	0.7102	0.8427
No log	2.1538	56	0.8288	0.5709	0.8288	0.9104
No log	2.2308	58	0.9133	0.5759	0.9133	0.9557
No log	2.3077	60	0.8281	0.6038	0.8281	0.9100
No log	2.3846	62	0.6920	0.6542	0.6920	0.8318
No log	2.4615	64	0.6607	0.6472	0.6607	0.8128
No log	2.5385	66	0.6817	0.7022	0.6817	0.8256
No log	2.6154	68	0.7592	0.6908	0.7592	0.8713
No log	2.6923	70	0.8782	0.6389	0.8782	0.9371
No log	2.7692	72	0.8614	0.6519	0.8614	0.9281
No log	2.8462	74	0.7744	0.6653	0.7744	0.8800
No log	2.9231	76	0.7364	0.6820	0.7364	0.8582
No log	3.0	78	0.7464	0.6575	0.7464	0.8639
No log	3.0769	80	0.8167	0.6225	0.8167	0.9037
No log	3.1538	82	0.9759	0.5685	0.9759	0.9879
No log	3.2308	84	0.9269	0.5750	0.9269	0.9627
No log	3.3077	86	0.8266	0.5896	0.8266	0.9092
No log	3.3846	88	0.7851	0.6236	0.7851	0.8861
No log	3.4615	90	0.7649	0.6776	0.7649	0.8746
No log	3.5385	92	0.7982	0.6935	0.7982	0.8934
No log	3.6154	94	0.8954	0.6764	0.8954	0.9463
No log	3.6923	96	0.8838	0.6985	0.8838	0.9401
No log	3.7692	98	0.8442	0.6621	0.8442	0.9188
No log	3.8462	100	0.7670	0.6575	0.7670	0.8758
No log	3.9231	102	0.7456	0.6664	0.7456	0.8635
No log	4.0	104	0.8494	0.6868	0.8494	0.9216
No log	4.0769	106	1.1239	0.6122	1.1239	1.0601
No log	4.1538	108	1.2556	0.5370	1.2556	1.1205
No log	4.2308	110	1.1872	0.5704	1.1872	1.0896
No log	4.3077	112	1.0735	0.5741	1.0735	1.0361
No log	4.3846	114	1.0512	0.5917	1.0512	1.0253
No log	4.4615	116	0.9832	0.6386	0.9832	0.9916
No log	4.5385	118	0.9283	0.6729	0.9283	0.9635
No log	4.6154	120	0.8713	0.6773	0.8713	0.9335
No log	4.6923	122	0.7458	0.7533	0.7458	0.8636
No log	4.7692	124	0.6855	0.7022	0.6855	0.8280
No log	4.8462	126	0.6928	0.7060	0.6928	0.8324
No log	4.9231	128	0.7132	0.7117	0.7132	0.8445
No log	5.0	130	0.7556	0.7239	0.7556	0.8693
No log	5.0769	132	0.8267	0.7058	0.8267	0.9092
No log	5.1538	134	0.8765	0.6909	0.8765	0.9362
No log	5.2308	136	0.8152	0.6892	0.8152	0.9029
No log	5.3077	138	0.7300	0.7020	0.7300	0.8544
No log	5.3846	140	0.6924	0.7048	0.6924	0.8321
No log	5.4615	142	0.6955	0.7074	0.6955	0.8339
No log	5.5385	144	0.7785	0.6960	0.7785	0.8823
No log	5.6154	146	0.9270	0.6540	0.9270	0.9628
No log	5.6923	148	1.1402	0.6336	1.1402	1.0678
No log	5.7692	150	1.2424	0.5908	1.2424	1.1146
No log	5.8462	152	1.2057	0.5893	1.2057	1.0981
No log	5.9231	154	1.1397	0.6047	1.1397	1.0676
No log	6.0	156	1.0019	0.6124	1.0019	1.0010
No log	6.0769	158	0.8706	0.6623	0.8706	0.9331
No log	6.1538	160	0.7781	0.6850	0.7781	0.8821
No log	6.2308	162	0.7331	0.7018	0.7331	0.8562
No log	6.3077	164	0.7477	0.6986	0.7477	0.8647
No log	6.3846	166	0.7971	0.6740	0.7971	0.8928
No log	6.4615	168	0.8513	0.6773	0.8513	0.9227
No log	6.5385	170	0.8897	0.6760	0.8897	0.9432
No log	6.6154	172	0.9072	0.6814	0.9072	0.9525
No log	6.6923	174	0.9914	0.6855	0.9914	0.9957
No log	6.7692	176	1.0320	0.6624	1.0320	1.0159
No log	6.8462	178	0.9614	0.6775	0.9614	0.9805
No log	6.9231	180	0.8943	0.6544	0.8943	0.9457
No log	7.0	182	0.8321	0.6809	0.8321	0.9122
No log	7.0769	184	0.7907	0.6723	0.7907	0.8892
No log	7.1538	186	0.7823	0.6833	0.7823	0.8845
No log	7.2308	188	0.7899	0.6826	0.7899	0.8888
No log	7.3077	190	0.7823	0.6826	0.7823	0.8845
No log	7.3846	192	0.7839	0.6826	0.7839	0.8854
No log	7.4615	194	0.8361	0.6868	0.8361	0.9144
No log	7.5385	196	0.8880	0.6570	0.8880	0.9423
No log	7.6154	198	0.8714	0.6627	0.8714	0.9335
No log	7.6923	200	0.8482	0.6633	0.8482	0.9210
No log	7.7692	202	0.8816	0.6570	0.8816	0.9389
No log	7.8462	204	0.9192	0.6622	0.9192	0.9588
No log	7.9231	206	0.9965	0.6842	0.9965	0.9982
No log	8.0	208	1.0667	0.6531	1.0667	1.0328
No log	8.0769	210	1.0524	0.6544	1.0524	1.0258
No log	8.1538	212	1.0121	0.6635	1.0121	1.0061
No log	8.2308	214	0.9458	0.6575	0.9458	0.9725
No log	8.3077	216	0.8921	0.6620	0.8921	0.9445
No log	8.3846	218	0.8535	0.6609	0.8535	0.9239
No log	8.4615	220	0.8395	0.6698	0.8395	0.9162
No log	8.5385	222	0.8453	0.6738	0.8453	0.9194
No log	8.6154	224	0.8683	0.6813	0.8683	0.9318
No log	8.6923	226	0.8866	0.6630	0.8866	0.9416
No log	8.7692	228	0.8967	0.6614	0.8967	0.9469
No log	8.8462	230	0.9190	0.6575	0.9190	0.9586
No log	8.9231	232	0.9250	0.6656	0.9250	0.9618
No log	9.0	234	0.9315	0.6656	0.9315	0.9652
No log	9.0769	236	0.9385	0.6656	0.9385	0.9688
No log	9.1538	238	0.9631	0.6656	0.9631	0.9814
No log	9.2308	240	0.9812	0.6436	0.9812	0.9906
No log	9.3077	242	0.9827	0.6436	0.9827	0.9913
No log	9.3846	244	0.9761	0.6562	0.9761	0.9880
No log	9.4615	246	0.9579	0.6562	0.9579	0.9787
No log	9.5385	248	0.9325	0.6518	0.9325	0.9657
No log	9.6154	250	0.9072	0.6605	0.9072	0.9525
No log	9.6923	252	0.8897	0.6612	0.8897	0.9432
No log	9.7692	254	0.8829	0.6612	0.8829	0.9396
No log	9.8462	256	0.8781	0.6612	0.8781	0.9371
No log	9.9231	258	0.8750	0.6627	0.8750	0.9354
No log	10.0	260	0.8731	0.6627	0.8731	0.9344

Framework versions

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