ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold2

genki10/ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold2

ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold2 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Feb 12, 2025
Updated: Feb 12, 2025
SHA: 19c81c53

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold2

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: 0.7259
Qwk: 0.4773
Mse: 0.7252
Rmse: 0.8516

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	4	8.9690	0.0	8.9697	2.9950
No log	2.0	8	5.7803	0.0348	5.7806	2.4043
No log	3.0	12	2.9523	0.0039	2.9528	1.7184
No log	4.0	16	1.6845	0.0797	1.6849	1.2980
No log	5.0	20	1.4160	0.0372	1.4164	1.1901
No log	6.0	24	1.0173	0.0515	1.0175	1.0087
No log	7.0	28	1.3699	0.0752	1.3702	1.1706
No log	8.0	32	0.9501	0.0968	0.9503	0.9748
No log	9.0	36	1.0454	0.2850	1.0454	1.0225
No log	10.0	40	0.9982	0.3293	0.9980	0.9990
No log	11.0	44	0.8615	0.3510	0.8613	0.9281
No log	12.0	48	1.1516	0.2742	1.1508	1.0728
No log	13.0	52	0.7124	0.3858	0.7121	0.8439
No log	14.0	56	0.8860	0.3819	0.8852	0.9409
No log	15.0	60	0.8855	0.4233	0.8844	0.9404
No log	16.0	64	0.9389	0.4005	0.9378	0.9684
No log	17.0	68	0.7158	0.4621	0.7148	0.8454
No log	18.0	72	1.3208	0.3014	1.3196	1.1488
No log	19.0	76	0.9843	0.3717	0.9830	0.9915
No log	20.0	80	0.8608	0.4116	0.8596	0.9272
No log	21.0	84	0.9034	0.3899	0.9024	0.9500
No log	22.0	88	0.9625	0.3788	0.9613	0.9805
No log	23.0	92	0.8656	0.4342	0.8645	0.9298
No log	24.0	96	0.8140	0.4737	0.8132	0.9018
No log	25.0	100	0.7620	0.4939	0.7613	0.8725
No log	26.0	104	0.8049	0.4854	0.8041	0.8967
No log	27.0	108	1.1709	0.3697	1.1701	1.0817
No log	28.0	112	0.7651	0.4705	0.7642	0.8742
No log	29.0	116	0.7552	0.4521	0.7543	0.8685
No log	30.0	120	0.9654	0.3916	0.9647	0.9822
No log	31.0	124	0.7620	0.4543	0.7613	0.8725
No log	32.0	128	0.7726	0.4453	0.7717	0.8785
No log	33.0	132	1.2172	0.3023	1.2166	1.1030
No log	34.0	136	0.7171	0.4623	0.7164	0.8464
No log	35.0	140	0.9899	0.3911	0.9892	0.9946
No log	36.0	144	0.7474	0.4624	0.7465	0.8640
No log	37.0	148	0.9503	0.4279	0.9496	0.9745
No log	38.0	152	0.7343	0.4521	0.7334	0.8564
No log	39.0	156	0.9444	0.4119	0.9438	0.9715
No log	40.0	160	0.7195	0.4776	0.7187	0.8478
No log	41.0	164	0.8223	0.4306	0.8213	0.9062
No log	42.0	168	1.1046	0.3598	1.1038	1.0506
No log	43.0	172	0.8350	0.4831	0.8342	0.9133
No log	44.0	176	0.7703	0.4656	0.7697	0.8773
No log	45.0	180	0.7259	0.4773	0.7252	0.8516

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 12, 2025
Updated: Feb 12, 2025