BERT_AugV8_k5_task1_organization_sp020_lw010_fold0

genki10/BERT_AugV8_k5_task1_organization_sp020_lw010_fold0

BERT_AugV8_k5_task1_organization_sp020_lw010_fold0 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: Mar 25, 2025
Updated: Mar 25, 2025
SHA: 693777e2

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Base models

Model card

From the Hugging Face model README

BERT_AugV8_k5_task1_organization_sp020_lw010_fold0

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: 0.8887
Qwk: 0.3516
Mse: 0.8887
Rmse: 0.9427

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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	4	9.8106	0.0	9.8106	3.1322
No log	2.0	8	4.8977	0.0231	4.8977	2.2131
No log	3.0	12	2.3924	0.1715	2.3924	1.5467
No log	4.0	16	1.3210	0.0419	1.3210	1.1493
No log	5.0	20	0.7866	0.3055	0.7866	0.8869
No log	6.0	24	1.2237	0.0419	1.2237	1.1062
No log	7.0	28	0.6373	0.3022	0.6373	0.7983
No log	8.0	32	1.1277	0.0805	1.1277	1.0619
No log	9.0	36	0.5714	0.3947	0.5714	0.7559
No log	10.0	40	0.6493	0.3778	0.6493	0.8058
No log	11.0	44	0.5386	0.4253	0.5386	0.7339
No log	12.0	48	0.6089	0.5046	0.6089	0.7803
No log	13.0	52	0.6323	0.4275	0.6323	0.7952
No log	14.0	56	0.7535	0.4635	0.7535	0.8681
No log	15.0	60	0.5836	0.4611	0.5836	0.7640
No log	16.0	64	0.6293	0.4380	0.6293	0.7933
No log	17.0	68	0.8329	0.3909	0.8329	0.9127
No log	18.0	72	0.5865	0.5108	0.5865	0.7659
No log	19.0	76	0.7626	0.4331	0.7626	0.8733
No log	20.0	80	0.7197	0.4773	0.7197	0.8483
No log	21.0	84	0.6766	0.4688	0.6766	0.8226
No log	22.0	88	0.8541	0.3815	0.8541	0.9242
No log	23.0	92	1.2586	0.2108	1.2586	1.1219
No log	24.0	96	0.6702	0.4550	0.6702	0.8186
No log	25.0	100	0.8194	0.3903	0.8194	0.9052
No log	26.0	104	0.6439	0.4642	0.6439	0.8024
No log	27.0	108	0.8190	0.3899	0.8190	0.9050
No log	28.0	112	0.6083	0.4737	0.6083	0.7799
No log	29.0	116	0.9547	0.3261	0.9547	0.9771
No log	30.0	120	0.6331	0.4680	0.6331	0.7957
No log	31.0	124	1.1624	0.2565	1.1624	1.0781
No log	32.0	128	0.5926	0.5061	0.5926	0.7698
No log	33.0	132	0.8887	0.3516	0.8887	0.9427

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 25, 2025
Updated: Mar 25, 2025