ArabicNewSplits5_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: 0.8693
• Qwk: 0.7257
• Mse: 0.8693
• Rmse: 0.9323

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	0.0513	2	2.2752	0.0279	2.2752	1.5084
No log	0.1026	4	1.6565	0.1837	1.6565	1.2870
No log	0.1538	6	1.4941	0.1677	1.4941	1.2223
No log	0.2051	8	1.4259	0.1120	1.4259	1.1941
No log	0.2564	10	1.2811	0.1733	1.2811	1.1318
No log	0.3077	12	1.2325	0.2047	1.2325	1.1102
No log	0.3590	14	1.2506	0.1888	1.2506	1.1183
No log	0.4103	16	1.3201	0.2774	1.3201	1.1490
No log	0.4615	18	1.2827	0.2787	1.2827	1.1326
No log	0.5128	20	1.2094	0.2084	1.2094	1.0997
No log	0.5641	22	1.1983	0.2997	1.1983	1.0947
No log	0.6154	24	1.1720	0.2907	1.1720	1.0826
No log	0.6667	26	1.1654	0.3111	1.1654	1.0795
No log	0.7179	28	1.1607	0.3243	1.1607	1.0774
No log	0.7692	30	1.1373	0.3227	1.1373	1.0665
No log	0.8205	32	1.1339	0.3324	1.1339	1.0648
No log	0.8718	34	1.1256	0.3543	1.1256	1.0609
No log	0.9231	36	1.1111	0.4048	1.1111	1.0541
No log	0.9744	38	1.1106	0.3918	1.1106	1.0538
No log	1.0256	40	1.1741	0.4071	1.1741	1.0836
No log	1.0769	42	1.2383	0.3713	1.2383	1.1128
No log	1.1282	44	1.3128	0.3403	1.3128	1.1458
No log	1.1795	46	1.2032	0.3249	1.2032	1.0969
No log	1.2308	48	1.1136	0.3544	1.1136	1.0553
No log	1.2821	50	1.0875	0.3756	1.0875	1.0428
No log	1.3333	52	1.1407	0.3359	1.1407	1.0680
No log	1.3846	54	1.2615	0.3687	1.2615	1.1232
No log	1.4359	56	1.3725	0.3364	1.3725	1.1716
No log	1.4872	58	1.3537	0.3208	1.3537	1.1635
No log	1.5385	60	1.2732	0.3241	1.2732	1.1283
No log	1.5897	62	1.2558	0.4091	1.2558	1.1206
No log	1.6410	64	1.3434	0.3849	1.3434	1.1590
No log	1.6923	66	1.4955	0.3419	1.4955	1.2229
No log	1.7436	68	1.4055	0.4127	1.4055	1.1855
No log	1.7949	70	1.2983	0.4129	1.2983	1.1394
No log	1.8462	72	1.1593	0.4502	1.1593	1.0767
No log	1.8974	74	1.1929	0.4391	1.1929	1.0922
No log	1.9487	76	1.1559	0.4615	1.1559	1.0751
No log	2.0	78	1.0849	0.5225	1.0849	1.0416
No log	2.0513	80	0.9946	0.4849	0.9946	0.9973
No log	2.1026	82	0.9787	0.4891	0.9787	0.9893
No log	2.1538	84	1.0953	0.5793	1.0953	1.0466
No log	2.2051	86	1.4251	0.4491	1.4251	1.1938
No log	2.2564	88	1.4772	0.3973	1.4772	1.2154
No log	2.3077	90	1.3445	0.4436	1.3445	1.1595
No log	2.3590	92	1.3064	0.4344	1.3064	1.1430
No log	2.4103	94	1.4649	0.4048	1.4649	1.2103
No log	2.4615	96	1.6585	0.3568	1.6585	1.2878
No log	2.5128	98	1.8460	0.2670	1.8460	1.3587
No log	2.5641	100	1.8258	0.2183	1.8258	1.3512
No log	2.6154	102	1.6464	0.3200	1.6464	1.2831
No log	2.6667	104	1.3506	0.3735	1.3506	1.1622
No log	2.7179	106	1.0430	0.5425	1.0430	1.0213
No log	2.7692	108	0.9169	0.5883	0.9169	0.9576
No log	2.8205	110	0.9789	0.5501	0.9789	0.9894
No log	2.8718	112	1.0994	0.5503	1.0994	1.0485
No log	2.9231	114	1.2082	0.5351	1.2082	1.0992
No log	2.9744	116	1.2419	0.5266	1.2419	1.1144
No log	3.0256	118	1.2143	0.5367	1.2143	1.1019
No log	3.0769	120	1.0086	0.6029	1.0086	1.0043
No log	3.1282	122	0.9324	0.6387	0.9324	0.9656
No log	3.1795	124	0.9361	0.6392	0.9361	0.9675
No log	3.2308	126	0.9798	0.5965	0.9798	0.9899
No log	3.2821	128	0.9136	0.6258	0.9136	0.9558
No log	3.3333	130	0.8494	0.6345	0.8494	0.9216
No log	3.3846	132	0.8220	0.6472	0.8220	0.9066
No log	3.4359	134	0.8598	0.6785	0.8598	0.9273
No log	3.4872	136	1.0389	0.6428	1.0389	1.0192
No log	3.5385	138	1.2365	0.5871	1.2365	1.1120
No log	3.5897	140	1.3012	0.5650	1.3012	1.1407
No log	3.6410	142	1.1481	0.6022	1.1481	1.0715
No log	3.6923	144	0.9641	0.6550	0.9641	0.9819
No log	3.7436	146	0.8348	0.6362	0.8348	0.9137
No log	3.7949	148	0.8196	0.6262	0.8196	0.9053
No log	3.8462	150	0.8750	0.6195	0.8750	0.9354
No log	3.8974	152	0.9557	0.6221	0.9557	0.9776
No log	3.9487	154	1.0158	0.6193	1.0158	1.0079
No log	4.0	156	1.0455	0.6425	1.0455	1.0225
No log	4.0513	158	1.0025	0.6456	1.0025	1.0013
No log	4.1026	160	0.9274	0.6476	0.9274	0.9630
No log	4.1538	162	0.8813	0.6643	0.8813	0.9388
No log	4.2051	164	0.9326	0.6550	0.9326	0.9657
No log	4.2564	166	0.9782	0.6638	0.9782	0.9890
No log	4.3077	168	1.0540	0.6542	1.0540	1.0266
No log	4.3590	170	1.0140	0.6542	1.0140	1.0070
No log	4.4103	172	0.9088	0.6929	0.9088	0.9533
No log	4.4615	174	0.8690	0.6874	0.8690	0.9322
No log	4.5128	176	0.8583	0.6794	0.8583	0.9265
No log	4.5641	178	0.8586	0.6788	0.8586	0.9266
No log	4.6154	180	0.8664	0.6466	0.8664	0.9308
No log	4.6667	182	0.8434	0.6645	0.8434	0.9184
No log	4.7179	184	0.8414	0.6636	0.8414	0.9173
No log	4.7692	186	0.8453	0.6697	0.8453	0.9194
No log	4.8205	188	0.8145	0.6716	0.8145	0.9025
No log	4.8718	190	0.8266	0.6613	0.8266	0.9092
No log	4.9231	192	0.7788	0.6795	0.7788	0.8825
No log	4.9744	194	0.7713	0.6697	0.7713	0.8782
No log	5.0256	196	0.8053	0.6862	0.8053	0.8974
No log	5.0769	198	0.8265	0.6451	0.8265	0.9091
No log	5.1282	200	0.8108	0.6772	0.8108	0.9005
No log	5.1795	202	0.8255	0.6911	0.8255	0.9085
No log	5.2308	204	0.8649	0.7058	0.8649	0.9300
No log	5.2821	206	0.9954	0.6497	0.9954	0.9977
No log	5.3333	208	1.0826	0.6200	1.0826	1.0405
No log	5.3846	210	1.0911	0.6094	1.0911	1.0446
No log	5.4359	212	1.0027	0.6493	1.0027	1.0013
No log	5.4872	214	0.8751	0.6898	0.8751	0.9354
No log	5.5385	216	0.7925	0.7282	0.7925	0.8902
No log	5.5897	218	0.7727	0.7268	0.7727	0.8791
No log	5.6410	220	0.7540	0.6980	0.7540	0.8684
No log	5.6923	222	0.7595	0.7150	0.7595	0.8715
No log	5.7436	224	0.8132	0.7220	0.8132	0.9018
No log	5.7949	226	0.9180	0.7005	0.9180	0.9581
No log	5.8462	228	0.9473	0.6944	0.9473	0.9733
No log	5.8974	230	0.8918	0.7020	0.8918	0.9444
No log	5.9487	232	0.8466	0.7120	0.8466	0.9201
No log	6.0	234	0.7884	0.7247	0.7884	0.8879
No log	6.0513	236	0.7613	0.7210	0.7613	0.8725
No log	6.1026	238	0.7482	0.7210	0.7482	0.8650
No log	6.1538	240	0.7657	0.7210	0.7657	0.8751
No log	6.2051	242	0.8113	0.7198	0.8113	0.9007
No log	6.2564	244	0.8466	0.6819	0.8466	0.9201
No log	6.3077	246	0.8675	0.6716	0.8675	0.9314
No log	6.3590	248	0.8870	0.6494	0.8870	0.9418
No log	6.4103	250	0.9041	0.6494	0.9041	0.9508
No log	6.4615	252	0.8500	0.6718	0.8500	0.9219
No log	6.5128	254	0.7916	0.6758	0.7916	0.8897
No log	6.5641	256	0.7697	0.6747	0.7697	0.8773
No log	6.6154	258	0.7771	0.6843	0.7771	0.8815
No log	6.6667	260	0.8297	0.6991	0.8297	0.9109
No log	6.7179	262	0.8463	0.7138	0.8463	0.9199
No log	6.7692	264	0.8666	0.7140	0.8666	0.9309
No log	6.8205	266	0.8598	0.7138	0.8598	0.9273
No log	6.8718	268	0.8416	0.7276	0.8416	0.9174
No log	6.9231	270	0.8627	0.7179	0.8627	0.9288
No log	6.9744	272	0.9005	0.6966	0.9005	0.9489
No log	7.0256	274	0.8795	0.7049	0.8795	0.9378
No log	7.0769	276	0.8110	0.7143	0.8110	0.9006
No log	7.1282	278	0.7568	0.7205	0.7568	0.8699
No log	7.1795	280	0.7216	0.7024	0.7216	0.8494
No log	7.2308	282	0.7281	0.7024	0.7281	0.8533
No log	7.2821	284	0.7700	0.7287	0.7700	0.8775
No log	7.3333	286	0.8354	0.7206	0.8354	0.9140
No log	7.3846	288	0.9470	0.7001	0.9470	0.9732
No log	7.4359	290	1.0129	0.6850	1.0129	1.0064
No log	7.4872	292	1.0089	0.6850	1.0089	1.0044
No log	7.5385	294	0.9506	0.6981	0.9506	0.9750
No log	7.5897	296	0.8795	0.7140	0.8795	0.9378
No log	7.6410	298	0.8234	0.7353	0.8234	0.9074
No log	7.6923	300	0.8085	0.7297	0.8085	0.8992
No log	7.7436	302	0.8290	0.7353	0.8290	0.9105
No log	7.7949	304	0.8581	0.7256	0.8581	0.9263
No log	7.8462	306	0.8454	0.7127	0.8454	0.9195
No log	7.8974	308	0.8116	0.7240	0.8116	0.9009
No log	7.9487	310	0.7785	0.7112	0.7785	0.8823
No log	8.0	312	0.7535	0.7155	0.7535	0.8680
No log	8.0513	314	0.7297	0.6974	0.7297	0.8542
No log	8.1026	316	0.7301	0.7016	0.7301	0.8545
No log	8.1538	318	0.7419	0.6974	0.7419	0.8614
No log	8.2051	320	0.7542	0.7026	0.7542	0.8685
No log	8.2564	322	0.7840	0.6884	0.7840	0.8854
No log	8.3077	324	0.8161	0.6960	0.8161	0.9034
No log	8.3590	326	0.8472	0.7100	0.8472	0.9205
No log	8.4103	328	0.8536	0.7004	0.8536	0.9239
No log	8.4615	330	0.8302	0.7142	0.8302	0.9112
No log	8.5128	332	0.8186	0.7142	0.8186	0.9048
No log	8.5641	334	0.8196	0.7142	0.8196	0.9053
No log	8.6154	336	0.8413	0.7202	0.8413	0.9172
No log	8.6667	338	0.8836	0.7165	0.8836	0.9400
No log	8.7179	340	0.9172	0.7073	0.9172	0.9577
No log	8.7692	342	0.9443	0.7073	0.9443	0.9718
No log	8.8205	344	0.9682	0.7160	0.9682	0.9840
No log	8.8718	346	0.9608	0.7160	0.9608	0.9802
No log	8.9231	348	0.9330	0.7073	0.9330	0.9659
No log	8.9744	350	0.8987	0.7165	0.8987	0.9480
No log	9.0256	352	0.8747	0.7257	0.8747	0.9353
No log	9.0769	354	0.8547	0.7297	0.8547	0.9245
No log	9.1282	356	0.8518	0.7242	0.8518	0.9229
No log	9.1795	358	0.8471	0.7242	0.8471	0.9204
No log	9.2308	360	0.8471	0.7201	0.8471	0.9204
No log	9.2821	362	0.8453	0.7123	0.8453	0.9194
No log	9.3333	364	0.8458	0.7202	0.8458	0.9197
No log	9.3846	366	0.8496	0.7256	0.8496	0.9217
No log	9.4359	368	0.8501	0.7256	0.8501	0.9220
No log	9.4872	370	0.8497	0.7256	0.8497	0.9218
No log	9.5385	372	0.8560	0.7257	0.8560	0.9252
No log	9.5897	374	0.8603	0.7257	0.8603	0.9275
No log	9.6410	376	0.8635	0.7257	0.8635	0.9293
No log	9.6923	378	0.8684	0.7257	0.8684	0.9319
No log	9.7436	380	0.8705	0.7257	0.8705	0.9330
No log	9.7949	382	0.8715	0.7257	0.8715	0.9335
No log	9.8462	384	0.8703	0.7257	0.8703	0.9329
No log	9.8974	386	0.8688	0.7257	0.8688	0.9321
No log	9.9487	388	0.8689	0.7257	0.8689	0.9322
No log	10.0	390	0.8693	0.7257	0.8693	0.9323

Framework versions

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