ArabicNewSplits6_FineTuningAraBERTFreeze_run1_AugV5_k1_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: 0.6891
• Qwk: 0.7374
• Mse: 0.6891
• Rmse: 0.8301

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: 16
• eval_batch_size: 16
• 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	7.7706	0.0068	7.7706	2.7876
No log	1.0	4	6.0654	0.0145	6.0654	2.4628
No log	1.5	6	4.7439	0.0390	4.7439	2.1780
No log	2.0	8	3.7109	0.0149	3.7109	1.9264
No log	2.5	10	2.8471	-0.0917	2.8471	1.6873
No log	3.0	12	2.1052	0.0648	2.1052	1.4509
No log	3.5	14	1.5541	0.1738	1.5541	1.2466
No log	4.0	16	1.2068	0.3127	1.2068	1.0986
No log	4.5	18	1.0347	0.4023	1.0347	1.0172
No log	5.0	20	0.9379	0.4190	0.9379	0.9684
No log	5.5	22	0.9041	0.4432	0.9041	0.9508
No log	6.0	24	0.8665	0.5108	0.8665	0.9309
No log	6.5	26	0.8293	0.5348	0.8293	0.9107
No log	7.0	28	0.7811	0.6222	0.7811	0.8838
No log	7.5	30	0.7577	0.6283	0.7577	0.8704
No log	8.0	32	0.7659	0.6477	0.7659	0.8752
No log	8.5	34	0.8664	0.6676	0.8664	0.9308
No log	9.0	36	0.8111	0.6576	0.8111	0.9006
No log	9.5	38	0.7348	0.6914	0.7348	0.8572
No log	10.0	40	0.7074	0.7125	0.7074	0.8411
No log	10.5	42	0.7056	0.7180	0.7056	0.8400
No log	11.0	44	0.6988	0.7144	0.6988	0.8359
No log	11.5	46	0.7138	0.7097	0.7138	0.8449
No log	12.0	48	0.6879	0.6962	0.6879	0.8294
No log	12.5	50	0.6879	0.6995	0.6879	0.8294
No log	13.0	52	0.6914	0.7022	0.6914	0.8315
No log	13.5	54	0.7232	0.6955	0.7232	0.8504
No log	14.0	56	0.7261	0.7203	0.7261	0.8521
No log	14.5	58	0.6761	0.7144	0.6761	0.8223
No log	15.0	60	0.6391	0.7013	0.6391	0.7994
No log	15.5	62	0.6525	0.7000	0.6525	0.8078
No log	16.0	64	0.6360	0.7011	0.6360	0.7975
No log	16.5	66	0.6248	0.7211	0.6248	0.7905
No log	17.0	68	0.6638	0.7347	0.6638	0.8148
No log	17.5	70	0.6840	0.7403	0.6840	0.8271
No log	18.0	72	0.6425	0.7340	0.6425	0.8016
No log	18.5	74	0.6706	0.6722	0.6706	0.8189
No log	19.0	76	0.6871	0.6609	0.6871	0.8289
No log	19.5	78	0.6406	0.6933	0.6406	0.8004
No log	20.0	80	0.6367	0.7365	0.6367	0.7979
No log	20.5	82	0.6376	0.7447	0.6376	0.7985
No log	21.0	84	0.6402	0.7226	0.6402	0.8001
No log	21.5	86	0.6675	0.6883	0.6675	0.8170
No log	22.0	88	0.6714	0.6926	0.6714	0.8194
No log	22.5	90	0.6511	0.6926	0.6511	0.8069
No log	23.0	92	0.6321	0.7461	0.6321	0.7950
No log	23.5	94	0.6338	0.7411	0.6338	0.7961
No log	24.0	96	0.6541	0.7290	0.6541	0.8087
No log	24.5	98	0.7312	0.6590	0.7312	0.8551
No log	25.0	100	0.7165	0.6703	0.7165	0.8464
No log	25.5	102	0.6538	0.7177	0.6538	0.8086
No log	26.0	104	0.6235	0.7475	0.6235	0.7896
No log	26.5	106	0.6846	0.7439	0.6846	0.8274
No log	27.0	108	0.6670	0.7486	0.6670	0.8167
No log	27.5	110	0.6269	0.7527	0.6269	0.7918
No log	28.0	112	0.7179	0.6732	0.7179	0.8473
No log	28.5	114	0.7636	0.6418	0.7636	0.8739
No log	29.0	116	0.7074	0.6695	0.7074	0.8410
No log	29.5	118	0.6413	0.7295	0.6413	0.8008
No log	30.0	120	0.6420	0.7494	0.6420	0.8012
No log	30.5	122	0.7000	0.7389	0.7000	0.8367
No log	31.0	124	0.6641	0.7362	0.6641	0.8149
No log	31.5	126	0.6167	0.7607	0.6167	0.7853
No log	32.0	128	0.6655	0.7105	0.6655	0.8158
No log	32.5	130	0.8067	0.6579	0.8067	0.8982
No log	33.0	132	0.8354	0.6527	0.8354	0.9140
No log	33.5	134	0.7383	0.6811	0.7383	0.8593
No log	34.0	136	0.6356	0.7229	0.6356	0.7973
No log	34.5	138	0.6169	0.7328	0.6169	0.7854
No log	35.0	140	0.6181	0.7403	0.6181	0.7862
No log	35.5	142	0.6215	0.7354	0.6215	0.7884
No log	36.0	144	0.6741	0.7251	0.6741	0.8210
No log	36.5	146	0.6903	0.7145	0.6903	0.8308
No log	37.0	148	0.6712	0.7199	0.6712	0.8192
No log	37.5	150	0.6368	0.7550	0.6368	0.7980
No log	38.0	152	0.6368	0.7635	0.6368	0.7980
No log	38.5	154	0.6406	0.7550	0.6406	0.8004
No log	39.0	156	0.6473	0.7577	0.6473	0.8046
No log	39.5	158	0.6595	0.7347	0.6595	0.8121
No log	40.0	160	0.6750	0.7342	0.6750	0.8216
No log	40.5	162	0.6966	0.7306	0.6966	0.8346
No log	41.0	164	0.6875	0.7306	0.6875	0.8291
No log	41.5	166	0.6499	0.7378	0.6499	0.8062
No log	42.0	168	0.6223	0.7555	0.6223	0.7888
No log	42.5	170	0.6143	0.7680	0.6143	0.7838
No log	43.0	172	0.6055	0.7476	0.6055	0.7781
No log	43.5	174	0.6111	0.7434	0.6111	0.7817
No log	44.0	176	0.6639	0.6975	0.6639	0.8148
No log	44.5	178	0.7180	0.6778	0.7180	0.8474
No log	45.0	180	0.6963	0.6676	0.6963	0.8345
No log	45.5	182	0.6527	0.7257	0.6527	0.8079
No log	46.0	184	0.6478	0.7299	0.6478	0.8049
No log	46.5	186	0.6344	0.7316	0.6344	0.7965
No log	47.0	188	0.6378	0.7502	0.6378	0.7986
No log	47.5	190	0.6551	0.7277	0.6551	0.8094
No log	48.0	192	0.6857	0.7307	0.6857	0.8281
No log	48.5	194	0.6937	0.7369	0.6937	0.8329
No log	49.0	196	0.6851	0.7263	0.6851	0.8277
No log	49.5	198	0.6998	0.7343	0.6998	0.8365
No log	50.0	200	0.6923	0.7343	0.6923	0.8321
No log	50.5	202	0.6852	0.7343	0.6852	0.8278
No log	51.0	204	0.6970	0.7326	0.6970	0.8349
No log	51.5	206	0.6792	0.7353	0.6792	0.8241
No log	52.0	208	0.6587	0.7295	0.6587	0.8116
No log	52.5	210	0.6452	0.7332	0.6452	0.8032
No log	53.0	212	0.6674	0.7379	0.6674	0.8169
No log	53.5	214	0.7396	0.6608	0.7396	0.8600
No log	54.0	216	0.8289	0.6382	0.8289	0.9104
No log	54.5	218	0.8419	0.6279	0.8419	0.9176
No log	55.0	220	0.7815	0.6441	0.7815	0.8840
No log	55.5	222	0.7179	0.6910	0.7179	0.8473
No log	56.0	224	0.6657	0.7352	0.6657	0.8159
No log	56.5	226	0.6589	0.7384	0.6589	0.8117
No log	57.0	228	0.6769	0.7358	0.6769	0.8228
No log	57.5	230	0.6919	0.7351	0.6919	0.8318
No log	58.0	232	0.7196	0.6979	0.7196	0.8483
No log	58.5	234	0.7273	0.6979	0.7273	0.8528
No log	59.0	236	0.7076	0.7367	0.7076	0.8412
No log	59.5	238	0.6848	0.7342	0.6848	0.8275
No log	60.0	240	0.6949	0.7357	0.6949	0.8336
No log	60.5	242	0.7346	0.6918	0.7346	0.8571
No log	61.0	244	0.7328	0.6918	0.7328	0.8560
No log	61.5	246	0.6961	0.7309	0.6961	0.8343
No log	62.0	248	0.6878	0.7330	0.6878	0.8294
No log	62.5	250	0.7071	0.6962	0.7071	0.8409
No log	63.0	252	0.7264	0.6792	0.7264	0.8523
No log	63.5	254	0.7218	0.6792	0.7218	0.8496
No log	64.0	256	0.6908	0.7024	0.6908	0.8311
No log	64.5	258	0.6750	0.6982	0.6750	0.8216
No log	65.0	260	0.6847	0.7109	0.6847	0.8275
No log	65.5	262	0.6967	0.7146	0.6967	0.8347
No log	66.0	264	0.6892	0.7202	0.6892	0.8302
No log	66.5	266	0.6568	0.7432	0.6568	0.8104
No log	67.0	268	0.6373	0.7291	0.6373	0.7983
No log	67.5	270	0.6363	0.7291	0.6363	0.7977
No log	68.0	272	0.6368	0.7291	0.6368	0.7980
No log	68.5	274	0.6311	0.7454	0.6311	0.7944
No log	69.0	276	0.6325	0.7471	0.6325	0.7953
No log	69.5	278	0.6428	0.7421	0.6428	0.8017
No log	70.0	280	0.6751	0.7197	0.6751	0.8217
No log	70.5	282	0.7038	0.7191	0.7038	0.8389
No log	71.0	284	0.7174	0.7239	0.7174	0.8470
No log	71.5	286	0.6930	0.7183	0.6930	0.8325
No log	72.0	288	0.6441	0.7289	0.6441	0.8025
No log	72.5	290	0.6163	0.7488	0.6163	0.7851
No log	73.0	292	0.6100	0.7505	0.6100	0.7810
No log	73.5	294	0.6186	0.7437	0.6186	0.7865
No log	74.0	296	0.6498	0.7396	0.6498	0.8061
No log	74.5	298	0.6993	0.7123	0.6993	0.8363
No log	75.0	300	0.7259	0.6841	0.7259	0.8520
No log	75.5	302	0.7129	0.7087	0.7129	0.8443
No log	76.0	304	0.6841	0.7086	0.6841	0.8271
No log	76.5	306	0.6760	0.7200	0.6760	0.8222
No log	77.0	308	0.6504	0.7309	0.6504	0.8065
No log	77.5	310	0.6382	0.7358	0.6382	0.7989
No log	78.0	312	0.6355	0.7299	0.6355	0.7972
No log	78.5	314	0.6322	0.7299	0.6322	0.7951
No log	79.0	316	0.6358	0.7299	0.6358	0.7974
No log	79.5	318	0.6451	0.7358	0.6451	0.8032
No log	80.0	320	0.6484	0.7358	0.6484	0.8052
No log	80.5	322	0.6439	0.7358	0.6439	0.8024
No log	81.0	324	0.6351	0.7426	0.6351	0.7969
No log	81.5	326	0.6442	0.7353	0.6442	0.8026
No log	82.0	328	0.6612	0.7369	0.6612	0.8131
No log	82.5	330	0.6639	0.7325	0.6639	0.8148
No log	83.0	332	0.6772	0.7319	0.6772	0.8229
No log	83.5	334	0.6931	0.7082	0.6931	0.8325
No log	84.0	336	0.7030	0.6899	0.7030	0.8384
No log	84.5	338	0.7081	0.6899	0.7081	0.8415
No log	85.0	340	0.7162	0.6854	0.7162	0.8463
No log	85.5	342	0.7230	0.6854	0.7230	0.8503
No log	86.0	344	0.7092	0.6817	0.7092	0.8421
No log	86.5	346	0.6850	0.7154	0.6850	0.8276
No log	87.0	348	0.6703	0.7417	0.6703	0.8187
No log	87.5	350	0.6677	0.7417	0.6677	0.8172
No log	88.0	352	0.6739	0.7417	0.6739	0.8209
No log	88.5	354	0.6834	0.7250	0.6834	0.8267
No log	89.0	356	0.6983	0.7162	0.6983	0.8357
No log	89.5	358	0.7189	0.6817	0.7189	0.8479
No log	90.0	360	0.7335	0.6854	0.7335	0.8564
No log	90.5	362	0.7470	0.6929	0.7470	0.8643
No log	91.0	364	0.7561	0.6992	0.7561	0.8696
No log	91.5	366	0.7606	0.6948	0.7606	0.8721
No log	92.0	368	0.7558	0.6992	0.7558	0.8693
No log	92.5	370	0.7461	0.6929	0.7461	0.8638
No log	93.0	372	0.7300	0.6854	0.7300	0.8544
No log	93.5	374	0.7156	0.6861	0.7156	0.8459
No log	94.0	376	0.7085	0.6950	0.7085	0.8417
No log	94.5	378	0.7002	0.7185	0.7002	0.8368
No log	95.0	380	0.6902	0.7374	0.6902	0.8308
No log	95.5	382	0.6826	0.7417	0.6826	0.8262
No log	96.0	384	0.6771	0.7417	0.6771	0.8229
No log	96.5	386	0.6749	0.7417	0.6749	0.8215
No log	97.0	388	0.6763	0.7417	0.6763	0.8224
No log	97.5	390	0.6789	0.7417	0.6789	0.8240
No log	98.0	392	0.6829	0.7417	0.6829	0.8264
No log	98.5	394	0.6863	0.7374	0.6863	0.8285
No log	99.0	396	0.6875	0.7374	0.6875	0.8292
No log	99.5	398	0.6885	0.7374	0.6885	0.8298
No log	100.0	400	0.6891	0.7374	0.6891	0.8301

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.2.0
• Tokenizers 0.19.1