Version2ASAP_FineTuningBERT_AugV5_k7_task1_organization_k7_k7_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: 0.8096
• Qwk: 0.4688
• Mse: 0.8092
• Rmse: 0.8995

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	6	6.7593	-0.0166	6.7567	2.5994
No log	2.0	12	2.8124	0.0	2.8105	1.6765
No log	3.0	18	1.3850	0.0211	1.3835	1.1762
No log	4.0	24	1.3523	0.0211	1.3508	1.1623
No log	5.0	30	1.3825	0.0211	1.3810	1.1751
No log	6.0	36	1.5523	0.0692	1.5507	1.2453
No log	7.0	42	1.0416	0.0544	1.0402	1.0199
No log	8.0	48	0.8870	0.0946	0.8857	0.9411
No log	9.0	54	0.9429	0.3091	0.9417	0.9704
No log	10.0	60	0.7973	0.4370	0.7966	0.8925
No log	11.0	66	0.8776	0.4012	0.8771	0.9365
No log	12.0	72	0.8850	0.4271	0.8846	0.9405
No log	13.0	78	0.6337	0.5483	0.6331	0.7957
No log	14.0	84	0.7078	0.4939	0.7072	0.8409
No log	15.0	90	0.8496	0.4513	0.8489	0.9214
No log	16.0	96	0.6935	0.5693	0.6927	0.8323
No log	17.0	102	0.7428	0.5449	0.7423	0.8616
No log	18.0	108	0.7684	0.5477	0.7678	0.8762
No log	19.0	114	0.8687	0.4619	0.8682	0.9318
No log	20.0	120	0.8017	0.4774	0.8011	0.8951
No log	21.0	126	0.8308	0.4970	0.8304	0.9113
No log	22.0	132	0.7241	0.5241	0.7236	0.8506
No log	23.0	138	0.8264	0.4991	0.8260	0.9088
No log	24.0	144	0.7283	0.5225	0.7276	0.8530
No log	25.0	150	0.7228	0.5450	0.7223	0.8499
No log	26.0	156	0.8071	0.4725	0.8066	0.8981
No log	27.0	162	0.8570	0.4521	0.8566	0.9255
No log	28.0	168	0.7176	0.5234	0.7172	0.8469
No log	29.0	174	0.7287	0.5449	0.7283	0.8534
No log	30.0	180	0.7625	0.4950	0.7621	0.8730
No log	31.0	186	0.8106	0.4377	0.8100	0.9000
No log	32.0	192	0.7509	0.4713	0.7503	0.8662
No log	33.0	198	0.8055	0.4597	0.8049	0.8972
No log	34.0	204	0.7804	0.4971	0.7799	0.8831
No log	35.0	210	0.7436	0.5011	0.7431	0.8620
No log	36.0	216	0.8096	0.4688	0.8092	0.8995

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.3.1
• Tokenizers 0.21.0