ArabicNewSplits6_FineTuningAraBERT_run3_AugV5_k5_task2_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: 0.7985
• Qwk: 0.5404
• Mse: 0.7985
• Rmse: 0.8936

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	4.1224	-0.0135	4.1224	2.0304
No log	0.1538	4	2.2528	0.0779	2.2528	1.5009
No log	0.2308	6	1.1384	0.0666	1.1384	1.0670
No log	0.3077	8	0.8578	-0.0409	0.8578	0.9262
No log	0.3846	10	0.7347	0.2198	0.7347	0.8572
No log	0.4615	12	0.7022	0.1987	0.7022	0.8380
No log	0.5385	14	0.7410	0.1343	0.7410	0.8608
No log	0.6154	16	0.6744	0.2120	0.6744	0.8212
No log	0.6923	18	0.6556	0.2461	0.6556	0.8097
No log	0.7692	20	0.6426	0.3014	0.6426	0.8016
No log	0.8462	22	0.6243	0.3300	0.6243	0.7901
No log	0.9231	24	0.6264	0.3611	0.6264	0.7915
No log	1.0	26	0.8066	0.2023	0.8066	0.8981
No log	1.0769	28	0.9178	0.1883	0.9178	0.9580
No log	1.1538	30	0.9135	0.2244	0.9135	0.9558
No log	1.2308	32	0.8456	0.1954	0.8456	0.9196
No log	1.3077	34	0.6726	0.3280	0.6726	0.8201
No log	1.3846	36	0.5635	0.4960	0.5635	0.7507
No log	1.4615	38	0.5389	0.5045	0.5389	0.7341
No log	1.5385	40	0.5418	0.4597	0.5418	0.7361
No log	1.6154	42	0.5813	0.4676	0.5813	0.7624
No log	1.6923	44	1.0424	0.2175	1.0424	1.0210
No log	1.7692	46	1.8282	0.1727	1.8282	1.3521
No log	1.8462	48	1.8828	0.1544	1.8828	1.3721
No log	1.9231	50	1.5085	0.1916	1.5085	1.2282
No log	2.0	52	0.9845	0.1803	0.9845	0.9922
No log	2.0769	54	0.6243	0.4241	0.6243	0.7901
No log	2.1538	56	0.5287	0.4654	0.5287	0.7271
No log	2.2308	58	0.5478	0.3975	0.5478	0.7402
No log	2.3077	60	0.6034	0.4267	0.6034	0.7768
No log	2.3846	62	0.5868	0.5028	0.5868	0.7660
No log	2.4615	64	0.5882	0.5521	0.5882	0.7669
No log	2.5385	66	1.0176	0.4097	1.0176	1.0088
No log	2.6154	68	1.6663	0.1931	1.6663	1.2909
No log	2.6923	70	1.6967	0.1948	1.6967	1.3026
No log	2.7692	72	1.3769	0.3003	1.3769	1.1734
No log	2.8462	74	0.9383	0.3249	0.9383	0.9687
No log	2.9231	76	0.6476	0.4034	0.6476	0.8047
No log	3.0	78	0.4963	0.5789	0.4963	0.7045
No log	3.0769	80	0.5302	0.5787	0.5302	0.7281
No log	3.1538	82	0.5519	0.5050	0.5519	0.7429
No log	3.2308	84	0.5204	0.5751	0.5204	0.7214
No log	3.3077	86	0.5270	0.4520	0.5270	0.7260
No log	3.3846	88	0.6660	0.3534	0.6660	0.8161
No log	3.4615	90	0.7646	0.2965	0.7646	0.8744
No log	3.5385	92	0.7954	0.3370	0.7954	0.8918
No log	3.6154	94	0.7198	0.4042	0.7198	0.8484
No log	3.6923	96	0.5870	0.4191	0.5870	0.7662
No log	3.7692	98	0.5114	0.5327	0.5114	0.7151
No log	3.8462	100	0.5116	0.6183	0.5116	0.7152
No log	3.9231	102	0.5649	0.5341	0.5649	0.7516
No log	4.0	104	0.7455	0.4663	0.7455	0.8634
No log	4.0769	106	0.9793	0.4286	0.9793	0.9896
No log	4.1538	108	1.0731	0.4075	1.0731	1.0359
No log	4.2308	110	0.9748	0.4338	0.9748	0.9873
No log	4.3077	112	0.7912	0.4417	0.7912	0.8895
No log	4.3846	114	0.7204	0.4561	0.7204	0.8488
No log	4.4615	116	0.6741	0.5443	0.6741	0.8211
No log	4.5385	118	0.7033	0.4796	0.7033	0.8386
No log	4.6154	120	0.7454	0.4619	0.7454	0.8634
No log	4.6923	122	0.7562	0.4662	0.7562	0.8696
No log	4.7692	124	0.7601	0.4920	0.7601	0.8718
No log	4.8462	126	0.8205	0.4714	0.8205	0.9058
No log	4.9231	128	0.9494	0.4511	0.9494	0.9744
No log	5.0	130	1.0350	0.4087	1.0350	1.0173
No log	5.0769	132	0.9608	0.4242	0.9608	0.9802
No log	5.1538	134	0.8639	0.5267	0.8639	0.9295
No log	5.2308	136	0.8597	0.5273	0.8597	0.9272
No log	5.3077	138	0.8726	0.5202	0.8726	0.9342
No log	5.3846	140	0.8607	0.5078	0.8607	0.9277
No log	5.4615	142	0.8540	0.5322	0.8540	0.9241
No log	5.5385	144	0.8726	0.5002	0.8726	0.9341
No log	5.6154	146	0.8799	0.4895	0.8799	0.9381
No log	5.6923	148	0.8782	0.5096	0.8782	0.9371
No log	5.7692	150	0.8466	0.5051	0.8466	0.9201
No log	5.8462	152	0.7802	0.5387	0.7802	0.8833
No log	5.9231	154	0.7439	0.5360	0.7439	0.8625
No log	6.0	156	0.7341	0.5523	0.7341	0.8568
No log	6.0769	158	0.7450	0.5691	0.7450	0.8632
No log	6.1538	160	0.7294	0.5619	0.7294	0.8541
No log	6.2308	162	0.7150	0.5754	0.7150	0.8456
No log	6.3077	164	0.7126	0.5663	0.7126	0.8441
No log	6.3846	166	0.7188	0.5553	0.7188	0.8478
No log	6.4615	168	0.7312	0.5805	0.7312	0.8551
No log	6.5385	170	0.7403	0.5681	0.7403	0.8604
No log	6.6154	172	0.7554	0.5680	0.7554	0.8691
No log	6.6923	174	0.7781	0.5680	0.7781	0.8821
No log	6.7692	176	0.7959	0.5579	0.7959	0.8921
No log	6.8462	178	0.8125	0.5553	0.8125	0.9014
No log	6.9231	180	0.8292	0.5551	0.8292	0.9106
No log	7.0	182	0.8347	0.5489	0.8347	0.9136
No log	7.0769	184	0.8312	0.5489	0.8312	0.9117
No log	7.1538	186	0.8140	0.5527	0.8140	0.9022
No log	7.2308	188	0.8003	0.5741	0.8003	0.8946
No log	7.3077	190	0.7879	0.5704	0.7879	0.8876
No log	7.3846	192	0.7762	0.5705	0.7762	0.8810
No log	7.4615	194	0.7652	0.5844	0.7652	0.8748
No log	7.5385	196	0.7627	0.5389	0.7627	0.8733
No log	7.6154	198	0.7831	0.5485	0.7831	0.8849
No log	7.6923	200	0.8147	0.5194	0.8147	0.9026
No log	7.7692	202	0.8264	0.5314	0.8264	0.9091
No log	7.8462	204	0.8162	0.5286	0.8162	0.9034
No log	7.9231	206	0.7970	0.5475	0.7970	0.8928
No log	8.0	208	0.7858	0.5440	0.7858	0.8865
No log	8.0769	210	0.8009	0.5753	0.8009	0.8949
No log	8.1538	212	0.8205	0.5308	0.8205	0.9058
No log	8.2308	214	0.8276	0.5308	0.8276	0.9097
No log	8.3077	216	0.8250	0.5484	0.8250	0.9083
No log	8.3846	218	0.8211	0.5615	0.8211	0.9062
No log	8.4615	220	0.8200	0.5404	0.8200	0.9055
No log	8.5385	222	0.8270	0.5443	0.8270	0.9094
No log	8.6154	224	0.8315	0.5598	0.8315	0.9119
No log	8.6923	226	0.8331	0.5598	0.8331	0.9127
No log	8.7692	228	0.8298	0.5490	0.8298	0.9109
No log	8.8462	230	0.8259	0.5443	0.8259	0.9088
No log	8.9231	232	0.8243	0.5454	0.8243	0.9079
No log	9.0	234	0.8209	0.5466	0.8209	0.9060
No log	9.0769	236	0.8192	0.5527	0.8192	0.9051
No log	9.1538	238	0.8174	0.5478	0.8174	0.9041
No log	9.2308	240	0.8172	0.5527	0.8172	0.9040
No log	9.3077	242	0.8159	0.5527	0.8159	0.9033
No log	9.3846	244	0.8126	0.5527	0.8126	0.9015
No log	9.4615	246	0.8083	0.5502	0.8083	0.8991
No log	9.5385	248	0.8052	0.5453	0.8052	0.8973
No log	9.6154	250	0.8029	0.5404	0.8029	0.8960
No log	9.6923	252	0.8013	0.5404	0.8013	0.8951
No log	9.7692	254	0.7999	0.5404	0.7999	0.8944
No log	9.8462	256	0.7991	0.5404	0.7991	0.8939
No log	9.9231	258	0.7988	0.5404	0.7988	0.8937
No log	10.0	260	0.7985	0.5404	0.7985	0.8936

Framework versions

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