ASAP_FineTuningBERT_AugV7_k15_task1_organization_k15_k15_fold1

genki10/ASAP_FineTuningBERT_AugV7_k15_task1_organization_k15_k15_fold1

ASAP_FineTuningBERT_AugV7_k15_task1_organization_k15_k15_fold1 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 9, 2025
Updated: Feb 9, 2025
SHA: 85da2459

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV7_k15_task1_organization_k15_k15_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: 0.6954
Qwk: 0.4603
Mse: 0.6950
Rmse: 0.8336

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	12	4.9970	0.0233	4.9949	2.2349
No log	2.0	24	1.4334	0.0583	1.4320	1.1967
No log	3.0	36	1.6026	0.1011	1.6012	1.2654
No log	4.0	48	1.7165	0.2022	1.7155	1.3098
No log	5.0	60	0.7413	0.4083	0.7405	0.8605
No log	6.0	72	0.8809	0.4252	0.8804	0.9383
No log	7.0	84	0.7878	0.4524	0.7871	0.8872
No log	8.0	96	1.0826	0.3515	1.0817	1.0400
No log	9.0	108	0.7235	0.4883	0.7231	0.8504
No log	10.0	120	1.1484	0.2931	1.1475	1.0712
No log	11.0	132	0.7830	0.4137	0.7828	0.8848
No log	12.0	144	1.0063	0.3173	1.0055	1.0027
No log	13.0	156	0.9564	0.3813	0.9555	0.9775
No log	14.0	168	1.0346	0.3759	1.0336	1.0167
No log	15.0	180	1.1705	0.2993	1.1695	1.0814
No log	16.0	192	0.7624	0.4344	0.7618	0.8728
No log	17.0	204	0.6466	0.4960	0.6462	0.8039
No log	18.0	216	0.7235	0.5045	0.7234	0.8505
No log	19.0	228	0.6792	0.4680	0.6788	0.8239
No log	20.0	240	0.9881	0.3216	0.9872	0.9936
No log	21.0	252	0.8751	0.3815	0.8742	0.9350
No log	22.0	264	0.7030	0.5103	0.7026	0.8382
No log	23.0	276	0.6929	0.4478	0.6924	0.8321
No log	24.0	288	0.7119	0.4827	0.7113	0.8434
No log	25.0	300	0.7597	0.4281	0.7590	0.8712
No log	26.0	312	0.7511	0.4049	0.7504	0.8663
No log	27.0	324	1.0040	0.3519	1.0031	1.0015
No log	28.0	336	0.6829	0.4647	0.6823	0.8260
No log	29.0	348	1.0143	0.3557	1.0134	1.0067
No log	30.0	360	0.7614	0.4417	0.7608	0.8722
No log	31.0	372	0.8772	0.3911	0.8765	0.9362
No log	32.0	384	0.6954	0.4603	0.6950	0.8336

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 9, 2025
Updated: Feb 9, 2025