ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_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: 1.2396
• Qwk: 0.4878
• Mse: 1.2396
• Rmse: 1.1134

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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.5	2	5.6252	0.1306	5.6252	2.3718
No log	1.0	4	3.3807	0.1667	3.3807	1.8387
No log	1.5	6	3.4798	0.0440	3.4798	1.8654
No log	2.0	8	2.4086	0.0462	2.4086	1.5520
No log	2.5	10	1.6055	0.2314	1.6055	1.2671
No log	3.0	12	1.5944	0.3226	1.5944	1.2627
No log	3.5	14	1.4046	0.3636	1.4046	1.1852
No log	4.0	16	1.4824	0.3273	1.4824	1.2176
No log	4.5	18	1.6225	0.2727	1.6225	1.2738
No log	5.0	20	1.6785	0.2243	1.6785	1.2956
No log	5.5	22	1.5509	0.3333	1.5509	1.2453
No log	6.0	24	1.5289	0.3590	1.5289	1.2365
No log	6.5	26	1.4958	0.2832	1.4958	1.2230
No log	7.0	28	1.4903	0.2222	1.4903	1.2208
No log	7.5	30	1.5937	0.2727	1.5937	1.2624
No log	8.0	32	1.4418	0.4138	1.4418	1.2007
No log	8.5	34	1.2709	0.4138	1.2709	1.1274
No log	9.0	36	1.2399	0.4667	1.2399	1.1135
No log	9.5	38	1.3255	0.4878	1.3255	1.1513
No log	10.0	40	1.4004	0.3419	1.4004	1.1834
No log	10.5	42	1.4805	0.3063	1.4805	1.2168
No log	11.0	44	1.4006	0.3478	1.4006	1.1835
No log	11.5	46	1.3231	0.3966	1.3231	1.1503
No log	12.0	48	1.2936	0.4628	1.2936	1.1374
No log	12.5	50	1.3307	0.3548	1.3307	1.1536
No log	13.0	52	1.3646	0.3333	1.3646	1.1682
No log	13.5	54	1.3762	0.3860	1.3762	1.1731
No log	14.0	56	1.2775	0.4348	1.2775	1.1303
No log	14.5	58	1.2391	0.4310	1.2391	1.1131
No log	15.0	60	1.2730	0.4576	1.2730	1.1283
No log	15.5	62	1.2301	0.4444	1.2301	1.1091
No log	16.0	64	1.2338	0.4561	1.2338	1.1108
No log	16.5	66	1.3113	0.4386	1.3113	1.1451
No log	17.0	68	1.2967	0.4696	1.2967	1.1387
No log	17.5	70	1.2399	0.5574	1.2399	1.1135
No log	18.0	72	1.1494	0.5323	1.1494	1.0721
No log	18.5	74	1.1259	0.5366	1.1259	1.0611
No log	19.0	76	1.1146	0.5397	1.1146	1.0558
No log	19.5	78	1.1460	0.5669	1.1460	1.0705
No log	20.0	80	1.2031	0.5669	1.2031	1.0969
No log	20.5	82	1.2098	0.528	1.2098	1.0999
No log	21.0	84	1.2279	0.5669	1.2279	1.1081
No log	21.5	86	1.2065	0.5827	1.2065	1.0984
No log	22.0	88	1.2249	0.5512	1.2249	1.1067
No log	22.5	90	1.2381	0.5827	1.2381	1.1127
No log	23.0	92	1.2412	0.5167	1.2412	1.1141
No log	23.5	94	1.2746	0.3604	1.2746	1.1290
No log	24.0	96	1.2844	0.375	1.2844	1.1333
No log	24.5	98	1.2651	0.4310	1.2651	1.1248
No log	25.0	100	1.3053	0.4677	1.3053	1.1425
No log	25.5	102	1.3902	0.4496	1.3902	1.1791
No log	26.0	104	1.3694	0.4496	1.3694	1.1702
No log	26.5	106	1.2779	0.4640	1.2779	1.1305
No log	27.0	108	1.2839	0.4576	1.2839	1.1331
No log	27.5	110	1.2863	0.4274	1.2863	1.1341
No log	28.0	112	1.2331	0.4833	1.2331	1.1104
No log	28.5	114	1.1793	0.512	1.1793	1.0860
No log	29.0	116	1.2114	0.5231	1.2114	1.1006
No log	29.5	118	1.2108	0.5426	1.2108	1.1004
No log	30.0	120	1.2409	0.5714	1.2409	1.1139
No log	30.5	122	1.2353	0.4538	1.2353	1.1114
No log	31.0	124	1.2565	0.4407	1.2565	1.1209
No log	31.5	126	1.2662	0.4576	1.2662	1.1253
No log	32.0	128	1.3135	0.4833	1.3135	1.1461
No log	32.5	130	1.3370	0.4667	1.3370	1.1563
No log	33.0	132	1.2492	0.5246	1.2492	1.1177
No log	33.5	134	1.1518	0.544	1.1518	1.0732
No log	34.0	136	1.1100	0.5	1.1100	1.0535
No log	34.5	138	1.1010	0.5082	1.1010	1.0493
No log	35.0	140	1.0934	0.496	1.0934	1.0457
No log	35.5	142	1.1680	0.5736	1.1680	1.0807
No log	36.0	144	1.2408	0.5312	1.2408	1.1139
No log	36.5	146	1.3105	0.5	1.3105	1.1448
No log	37.0	148	1.3443	0.5	1.3443	1.1594
No log	37.5	150	1.2811	0.5385	1.2811	1.1319
No log	38.0	152	1.1637	0.5692	1.1637	1.0787
No log	38.5	154	1.0743	0.5781	1.0743	1.0365
No log	39.0	156	1.0397	0.5781	1.0397	1.0197
No log	39.5	158	1.0621	0.5846	1.0621	1.0306
No log	40.0	160	1.0823	0.5938	1.0823	1.0404
No log	40.5	162	1.1186	0.5938	1.1186	1.0576
No log	41.0	164	1.1197	0.5984	1.1197	1.0582
No log	41.5	166	1.1330	0.5538	1.1330	1.0644
No log	42.0	168	1.1154	0.5827	1.1154	1.0561
No log	42.5	170	1.1310	0.5556	1.1310	1.0635
No log	43.0	172	1.1718	0.5041	1.1718	1.0825
No log	43.5	174	1.1747	0.544	1.1747	1.0838
No log	44.0	176	1.2106	0.56	1.2106	1.1003
No log	44.5	178	1.2401	0.5528	1.2401	1.1136
No log	45.0	180	1.2525	0.5528	1.2525	1.1191
No log	45.5	182	1.2113	0.5484	1.2113	1.1006
No log	46.0	184	1.1603	0.5082	1.1603	1.0772
No log	46.5	186	1.1315	0.4333	1.1315	1.0637
No log	47.0	188	1.1155	0.5041	1.1155	1.0562
No log	47.5	190	1.1367	0.5556	1.1367	1.0662
No log	48.0	192	1.2453	0.5197	1.2453	1.1159
No log	48.5	194	1.3105	0.4697	1.3105	1.1448
No log	49.0	196	1.3095	0.4662	1.3095	1.1443
No log	49.5	198	1.2975	0.4733	1.2975	1.1391
No log	50.0	200	1.2273	0.5079	1.2273	1.1079
No log	50.5	202	1.1865	0.6032	1.1865	1.0893
No log	51.0	204	1.1844	0.576	1.1844	1.0883
No log	51.5	206	1.1913	0.576	1.1913	1.0915
No log	52.0	208	1.2184	0.5645	1.2184	1.1038
No log	52.5	210	1.2323	0.5645	1.2323	1.1101
No log	53.0	212	1.2454	0.544	1.2454	1.1160
No log	53.5	214	1.2460	0.5246	1.2460	1.1162
No log	54.0	216	1.2373	0.4874	1.2373	1.1124
No log	54.5	218	1.2291	0.4538	1.2291	1.1086
No log	55.0	220	1.2581	0.4576	1.2581	1.1216
No log	55.5	222	1.2809	0.4274	1.2809	1.1318
No log	56.0	224	1.2858	0.4407	1.2858	1.1339
No log	56.5	226	1.2929	0.528	1.2929	1.1371
No log	57.0	228	1.2858	0.528	1.2858	1.1339
No log	57.5	230	1.2721	0.528	1.2721	1.1279
No log	58.0	232	1.2687	0.528	1.2687	1.1263
No log	58.5	234	1.2553	0.5041	1.2553	1.1204
No log	59.0	236	1.2258	0.5082	1.2258	1.1071
No log	59.5	238	1.2095	0.4793	1.2095	1.0998
No log	60.0	240	1.2071	0.4918	1.2071	1.0987
No log	60.5	242	1.2066	0.4500	1.2066	1.0985
No log	61.0	244	1.2157	0.4202	1.2157	1.1026
No log	61.5	246	1.2428	0.4370	1.2428	1.1148
No log	62.0	248	1.2778	0.4237	1.2777	1.1304
No log	62.5	250	1.2802	0.4274	1.2802	1.1315
No log	63.0	252	1.2618	0.4407	1.2618	1.1233
No log	63.5	254	1.2366	0.4706	1.2366	1.1120
No log	64.0	256	1.2192	0.4959	1.2192	1.1042
No log	64.5	258	1.1971	0.4918	1.1971	1.0941
No log	65.0	260	1.1786	0.4878	1.1786	1.0856
No log	65.5	262	1.1971	0.5203	1.1971	1.0941
No log	66.0	264	1.2277	0.5323	1.2277	1.1080
No log	66.5	266	1.2423	0.5238	1.2423	1.1146
No log	67.0	268	1.2468	0.512	1.2468	1.1166
No log	67.5	270	1.2185	0.5366	1.2185	1.1039
No log	68.0	272	1.1761	0.5203	1.1761	1.0845
No log	68.5	274	1.1532	0.5203	1.1532	1.0739
No log	69.0	276	1.1399	0.5161	1.1399	1.0677
No log	69.5	278	1.1360	0.5161	1.1360	1.0658
No log	70.0	280	1.1397	0.5203	1.1397	1.0676
No log	70.5	282	1.1534	0.5203	1.1534	1.0740
No log	71.0	284	1.1613	0.5203	1.1613	1.0777
No log	71.5	286	1.1943	0.4959	1.1943	1.0928
No log	72.0	288	1.2389	0.5246	1.2389	1.1131
No log	72.5	290	1.2683	0.5	1.2683	1.1262
No log	73.0	292	1.2686	0.4715	1.2686	1.1263
No log	73.5	294	1.2673	0.4754	1.2673	1.1258
No log	74.0	296	1.2666	0.4959	1.2666	1.1254
No log	74.5	298	1.2506	0.4833	1.2506	1.1183
No log	75.0	300	1.2363	0.4576	1.2363	1.1119
No log	75.5	302	1.2410	0.4538	1.2410	1.1140
No log	76.0	304	1.2528	0.4576	1.2528	1.1193
No log	76.5	306	1.2605	0.4274	1.2605	1.1227
No log	77.0	308	1.2698	0.4444	1.2698	1.1269
No log	77.5	310	1.2674	0.4576	1.2674	1.1258
No log	78.0	312	1.2765	0.4833	1.2765	1.1298
No log	78.5	314	1.3051	0.4833	1.3051	1.1424
No log	79.0	316	1.3329	0.4333	1.3329	1.1545
No log	79.5	318	1.3381	0.4628	1.3381	1.1568
No log	80.0	320	1.3405	0.4590	1.3405	1.1578
No log	80.5	322	1.3331	0.4878	1.3331	1.1546
No log	81.0	324	1.3162	0.4878	1.3162	1.1472
No log	81.5	326	1.2878	0.4754	1.2878	1.1348
No log	82.0	328	1.2678	0.5041	1.2678	1.1260
No log	82.5	330	1.2498	0.5246	1.2498	1.1180
No log	83.0	332	1.2452	0.5246	1.2452	1.1159
No log	83.5	334	1.2430	0.5124	1.2430	1.1149
No log	84.0	336	1.2449	0.4833	1.2449	1.1158
No log	84.5	338	1.2533	0.4833	1.2533	1.1195
No log	85.0	340	1.2549	0.5124	1.2549	1.1202
No log	85.5	342	1.2549	0.5203	1.2549	1.1202
No log	86.0	344	1.2412	0.5124	1.2412	1.1141
No log	86.5	346	1.2375	0.5124	1.2375	1.1124
No log	87.0	348	1.2376	0.5124	1.2376	1.1125
No log	87.5	350	1.2396	0.4833	1.2396	1.1134
No log	88.0	352	1.2462	0.4833	1.2462	1.1163
No log	88.5	354	1.2528	0.4833	1.2528	1.1193
No log	89.0	356	1.2570	0.4918	1.2570	1.1211
No log	89.5	358	1.2527	0.4918	1.2527	1.1192
No log	90.0	360	1.2464	0.4833	1.2464	1.1164
No log	90.5	362	1.2377	0.4833	1.2377	1.1125
No log	91.0	364	1.2301	0.4833	1.2301	1.1091
No log	91.5	366	1.2256	0.4833	1.2256	1.1071
No log	92.0	368	1.2272	0.4833	1.2272	1.1078
No log	92.5	370	1.2283	0.4833	1.2283	1.1083
No log	93.0	372	1.2304	0.4833	1.2304	1.1092
No log	93.5	374	1.2337	0.5124	1.2337	1.1107
No log	94.0	376	1.2340	0.5124	1.2340	1.1109
No log	94.5	378	1.2368	0.4918	1.2368	1.1121
No log	95.0	380	1.2405	0.4918	1.2405	1.1138
No log	95.5	382	1.2438	0.4918	1.2438	1.1152
No log	96.0	384	1.2437	0.4918	1.2437	1.1152
No log	96.5	386	1.2422	0.4878	1.2422	1.1145
No log	97.0	388	1.2410	0.4878	1.2410	1.1140
No log	97.5	390	1.2405	0.4878	1.2405	1.1138
No log	98.0	392	1.2389	0.4878	1.2389	1.1131
No log	98.5	394	1.2393	0.4878	1.2393	1.1132
No log	99.0	396	1.2401	0.4878	1.2401	1.1136
No log	99.5	398	1.2399	0.4878	1.2399	1.1135
No log	100.0	400	1.2396	0.4878	1.2396	1.1134

Framework versions

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