Version_concise_ASAP_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold0

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6169
• Qwk: 0.5381
• Mse: 0.6169
• Rmse: 0.7854

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	5	7.0689	0.0	7.0689	2.6587
No log	2.0	10	4.9016	0.0115	4.9016	2.2140
No log	3.0	15	2.8927	0.0	2.8927	1.7008
No log	4.0	20	1.5074	0.0316	1.5074	1.2278
No log	5.0	25	1.0464	0.0316	1.0464	1.0229
No log	6.0	30	1.3228	0.0675	1.3228	1.1501
No log	7.0	35	1.1538	0.1546	1.1538	1.0741
No log	8.0	40	0.7206	0.4426	0.7206	0.8489
No log	9.0	45	0.6296	0.4904	0.6296	0.7935
No log	10.0	50	0.7322	0.4464	0.7322	0.8557
No log	11.0	55	0.6800	0.4356	0.6800	0.8246
No log	12.0	60	0.6277	0.3744	0.6277	0.7923
No log	13.0	65	0.6225	0.5098	0.6225	0.7890
No log	14.0	70	0.6623	0.5184	0.6623	0.8138
No log	15.0	75	0.6594	0.5071	0.6594	0.8120
No log	16.0	80	0.6936	0.4945	0.6936	0.8328
No log	17.0	85	0.7398	0.5111	0.7398	0.8601
No log	18.0	90	0.7472	0.5039	0.7472	0.8644
No log	19.0	95	0.7819	0.5012	0.7819	0.8842
No log	20.0	100	0.7144	0.4763	0.7144	0.8452
No log	21.0	105	0.6969	0.5092	0.6969	0.8348
No log	22.0	110	0.6896	0.5343	0.6896	0.8304
No log	23.0	115	0.6530	0.5288	0.6530	0.8081
No log	24.0	120	0.6753	0.5294	0.6753	0.8217
No log	25.0	125	0.7361	0.5046	0.7361	0.8579
No log	26.0	130	0.6318	0.5083	0.6318	0.7949
No log	27.0	135	0.6690	0.5301	0.6690	0.8179
No log	28.0	140	0.7393	0.5132	0.7393	0.8598
No log	29.0	145	0.6392	0.5346	0.6392	0.7995
No log	30.0	150	0.7088	0.5300	0.7088	0.8419
No log	31.0	155	0.6546	0.5406	0.6546	0.8091
No log	32.0	160	0.8006	0.5092	0.8006	0.8948
No log	33.0	165	0.8333	0.4604	0.8333	0.9128
No log	34.0	170	0.6704	0.5021	0.6704	0.8188
No log	35.0	175	0.6613	0.5267	0.6613	0.8132
No log	36.0	180	0.6717	0.5359	0.6717	0.8196
No log	37.0	185	0.6712	0.4896	0.6712	0.8193
No log	38.0	190	0.8100	0.4679	0.8100	0.9000
No log	39.0	195	0.6176	0.5379	0.6176	0.7859
No log	40.0	200	0.6463	0.5061	0.6463	0.8039
No log	41.0	205	0.6693	0.5321	0.6693	0.8181
No log	42.0	210	0.6689	0.5236	0.6689	0.8179
No log	43.0	215	0.6338	0.5252	0.6338	0.7961
No log	44.0	220	0.7406	0.5237	0.7406	0.8606
No log	45.0	225	0.5935	0.5121	0.5935	0.7704
No log	46.0	230	0.6783	0.5252	0.6783	0.8236
No log	47.0	235	0.6043	0.5096	0.6043	0.7774
No log	48.0	240	0.6243	0.5496	0.6243	0.7901
No log	49.0	245	0.7634	0.5060	0.7634	0.8737
No log	50.0	250	0.6076	0.5324	0.6076	0.7795
No log	51.0	255	0.7197	0.5196	0.7197	0.8483
No log	52.0	260	0.6960	0.5214	0.6960	0.8343
No log	53.0	265	0.6090	0.5434	0.6090	0.7804
No log	54.0	270	0.6279	0.5343	0.6279	0.7924
No log	55.0	275	0.6618	0.5277	0.6618	0.8135
No log	56.0	280	0.6316	0.5271	0.6316	0.7947
No log	57.0	285	0.6353	0.5463	0.6353	0.7971
No log	58.0	290	0.6733	0.5251	0.6733	0.8206
No log	59.0	295	0.6261	0.5425	0.6261	0.7912
No log	60.0	300	0.7170	0.5219	0.7170	0.8467
No log	61.0	305	0.6152	0.5364	0.6152	0.7844
No log	62.0	310	0.5982	0.5410	0.5982	0.7734
No log	63.0	315	0.6448	0.5292	0.6448	0.8030
No log	64.0	320	0.6152	0.5622	0.6152	0.7843
No log	65.0	325	0.6329	0.5325	0.6329	0.7955
No log	66.0	330	0.6132	0.5286	0.6132	0.7831
No log	67.0	335	0.6760	0.5254	0.6760	0.8222
No log	68.0	340	0.6107	0.5510	0.6107	0.7815
No log	69.0	345	0.6247	0.5379	0.6247	0.7904
No log	70.0	350	0.6375	0.5292	0.6375	0.7984
No log	71.0	355	0.6433	0.5269	0.6433	0.8020
No log	72.0	360	0.6793	0.5156	0.6793	0.8242
No log	73.0	365	0.6227	0.5353	0.6227	0.7891
No log	74.0	370	0.6099	0.5383	0.6099	0.7810
No log	75.0	375	0.6483	0.5372	0.6483	0.8052
No log	76.0	380	0.6201	0.5341	0.6201	0.7875
No log	77.0	385	0.6398	0.5359	0.6398	0.7999
No log	78.0	390	0.6274	0.5340	0.6274	0.7921
No log	79.0	395	0.6400	0.5378	0.6400	0.8000
No log	80.0	400	0.6308	0.5274	0.6308	0.7942
No log	81.0	405	0.6584	0.5259	0.6584	0.8114
No log	82.0	410	0.6142	0.5321	0.6142	0.7837
No log	83.0	415	0.6236	0.5295	0.6236	0.7897
No log	84.0	420	0.6169	0.5381	0.6169	0.7854

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0