ASAP_FineTuningBERT_AugV9_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: 1.3803
• Qwk: 0.1877
• Mse: 1.3791
• Rmse: 1.1743

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	9.1711	0.0	9.1688	3.0280
No log	2.0	12	3.9123	0.0137	3.9106	1.9775
No log	3.0	18	1.7712	0.0631	1.7698	1.3303
No log	4.0	24	1.7817	0.0	1.7802	1.3343
No log	5.0	30	1.9004	0.0430	1.8986	1.3779
No log	6.0	36	1.3898	0.0106	1.3884	1.1783
No log	7.0	42	1.7560	0.1390	1.7543	1.3245
No log	8.0	48	0.9744	0.0211	0.9732	0.9865
No log	9.0	54	1.4067	0.0990	1.4052	1.1854
No log	10.0	60	1.4483	0.1130	1.4466	1.2027
No log	11.0	66	1.6967	0.1249	1.6949	1.3019
No log	12.0	72	0.8791	0.1599	0.8779	0.9370
No log	13.0	78	0.7974	0.2771	0.7965	0.8925
No log	14.0	84	1.7696	0.1539	1.7680	1.3296
No log	15.0	90	0.9746	0.3078	0.9737	0.9867
No log	16.0	96	0.9882	0.2651	0.9875	0.9937
No log	17.0	102	0.9887	0.3478	0.9880	0.9940
No log	18.0	108	1.0116	0.2862	1.0106	1.0053
No log	19.0	114	0.8353	0.4041	0.8346	0.9136
No log	20.0	120	0.9021	0.2955	0.9014	0.9494
No log	21.0	126	1.0918	0.2629	1.0910	1.0445
No log	22.0	132	1.2718	0.1373	1.2706	1.1272
No log	23.0	138	0.8633	0.3928	0.8628	0.9289
No log	24.0	144	0.9625	0.3139	0.9619	0.9808
No log	25.0	150	0.8328	0.4016	0.8323	0.9123
No log	26.0	156	1.0061	0.2679	1.0055	1.0027
No log	27.0	162	1.2622	0.1962	1.2610	1.1229
No log	28.0	168	1.4212	0.1558	1.4199	1.1916
No log	29.0	174	1.4905	0.2123	1.4894	1.2204
No log	30.0	180	0.9403	0.2741	0.9398	0.9694
No log	31.0	186	1.0260	0.1886	1.0253	1.0126
No log	32.0	192	1.3030	0.2263	1.3019	1.1410
No log	33.0	198	1.1928	0.2266	1.1918	1.0917
No log	34.0	204	0.9994	0.2948	0.9988	0.9994
No log	35.0	210	0.9311	0.2985	0.9304	0.9646
No log	36.0	216	0.9486	0.3148	0.9481	0.9737
No log	37.0	222	0.9863	0.2722	0.9856	0.9928
No log	38.0	228	1.0054	0.2566	1.0048	1.0024
No log	39.0	234	1.3803	0.1877	1.3791	1.1743

Framework versions

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