Version_weird_ASAP_FineTuningBERT_AugV12_k2_task1_organization_k2_k2_fold1

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: 0.7647
• Qwk: 0.6248
• Mse: 0.7641
• Rmse: 0.8741

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	1	12.9945	-0.0009	12.9914	3.6044
No log	2.0	2	10.6042	0.0048	10.6014	3.2560
No log	3.0	3	9.8705	0.0	9.8678	3.1413
No log	4.0	4	9.5081	0.0	9.5056	3.0831
No log	5.0	5	9.2023	0.0	9.1998	3.0331
No log	6.0	6	8.8690	0.0	8.8666	2.9777
No log	7.0	7	8.5012	0.0	8.4988	2.9153
No log	8.0	8	8.1227	0.0	8.1202	2.8496
No log	9.0	9	7.7550	0.0	7.7526	2.7843
No log	10.0	10	7.4029	0.0	7.4006	2.7204
No log	11.0	11	7.0634	0.0	7.0611	2.6573
No log	12.0	12	6.7269	0.0	6.7245	2.5932
No log	13.0	13	6.3840	0.0	6.3816	2.5262
No log	14.0	14	6.0262	0.0	6.0239	2.4544
No log	15.0	15	5.6446	0.0342	5.6423	2.3754
No log	16.0	16	5.2326	0.0040	5.2304	2.2870
No log	17.0	17	4.7840	0.0	4.7818	2.1867
No log	18.0	18	4.3190	0.0	4.3169	2.0777
No log	19.0	19	3.8879	0.0	3.8860	1.9713
No log	20.0	20	3.5515	0.0	3.5496	1.8840
No log	21.0	21	3.2951	0.0	3.2933	1.8148
No log	22.0	22	2.9814	0.0	2.9796	1.7262
No log	23.0	23	2.6569	0.0	2.6552	1.6295
No log	24.0	24	2.3989	0.0159	2.3972	1.5483
No log	25.0	25	2.2007	0.1583	2.1990	1.4829
No log	26.0	26	2.0202	0.0645	2.0185	1.4207
No log	27.0	27	1.8402	0.0315	1.8386	1.3559
No log	28.0	28	1.6671	0.0	1.6656	1.2906
No log	29.0	29	1.5086	0.0	1.5071	1.2277
No log	30.0	30	1.3819	0.0	1.3804	1.1749
No log	31.0	31	1.2597	0.0	1.2583	1.1217
No log	32.0	32	1.1573	0.0	1.1559	1.0751
No log	33.0	33	1.0691	0.0106	1.0677	1.0333
No log	34.0	34	0.9995	0.0106	0.9981	0.9991
No log	35.0	35	0.9420	0.0106	0.9407	0.9699
No log	36.0	36	0.8797	0.0418	0.8785	0.9373
No log	37.0	37	0.8129	0.4000	0.8117	0.9009
No log	38.0	38	0.7496	0.4294	0.7484	0.8651
No log	39.0	39	0.7153	0.3948	0.7141	0.8451
No log	40.0	40	0.6790	0.4081	0.6779	0.8233
No log	41.0	41	0.6233	0.4693	0.6220	0.7887
No log	42.0	42	0.6096	0.4565	0.6085	0.7801
No log	43.0	43	0.6074	0.4305	0.6063	0.7787
No log	44.0	44	0.6055	0.4463	0.6045	0.7775
No log	45.0	45	0.6127	0.4553	0.6116	0.7821
No log	46.0	46	0.6533	0.4316	0.6523	0.8076
No log	47.0	47	0.5886	0.5032	0.5876	0.7665
No log	48.0	48	0.5901	0.5080	0.5891	0.7675
No log	49.0	49	0.5596	0.5159	0.5586	0.7474
No log	50.0	50	0.5856	0.5195	0.5846	0.7646
No log	51.0	51	0.5563	0.5180	0.5553	0.7452
No log	52.0	52	0.4964	0.5587	0.4953	0.7038
No log	53.0	53	0.6097	0.5822	0.6089	0.7803
No log	54.0	54	0.6799	0.5524	0.6791	0.8241
No log	55.0	55	0.6005	0.6163	0.5997	0.7744
No log	56.0	56	0.5423	0.6463	0.5415	0.7359
No log	57.0	57	0.6460	0.5882	0.6453	0.8033
No log	58.0	58	0.6955	0.5639	0.6948	0.8336
No log	59.0	59	0.6869	0.5781	0.6863	0.8284
No log	60.0	60	0.7373	0.5690	0.7367	0.8583
No log	61.0	61	0.7946	0.5518	0.7940	0.8910
No log	62.0	62	0.7015	0.5925	0.7009	0.8372
No log	63.0	63	0.5553	0.6544	0.5544	0.7446
No log	64.0	64	0.6278	0.6355	0.6271	0.7919
No log	65.0	65	0.8951	0.5447	0.8945	0.9458
No log	66.0	66	0.9335	0.5336	0.9329	0.9658
No log	67.0	67	0.7709	0.6001	0.7703	0.8777
No log	68.0	68	0.5875	0.6481	0.5867	0.7659
No log	69.0	69	0.6085	0.6299	0.6076	0.7795
No log	70.0	70	0.8306	0.5881	0.8299	0.9110
No log	71.0	71	1.1352	0.5027	1.1346	1.0652
No log	72.0	72	1.1640	0.5027	1.1634	1.0786
No log	73.0	73	0.9588	0.5623	0.9583	0.9789
No log	74.0	74	0.6794	0.6233	0.6787	0.8238
No log	75.0	75	0.6297	0.6394	0.6290	0.7931
No log	76.0	76	0.7217	0.6124	0.7210	0.8491
No log	77.0	77	0.9711	0.5719	0.9706	0.9852
No log	78.0	78	1.1204	0.5343	1.1200	1.0583
No log	79.0	79	1.1497	0.5340	1.1493	1.0720
No log	80.0	80	1.0188	0.5704	1.0184	1.0091
No log	81.0	81	0.7888	0.6257	0.7882	0.8878
No log	82.0	82	0.7215	0.6283	0.7208	0.8490
No log	83.0	83	0.7647	0.6248	0.7641	0.8741

Framework versions

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