bert-base-uncased-finetuned-filtered-0609 – AI Model by YeRyeongLee | AlphaNeural AI

You can deploy this model and start earning money today!

YeRyeongLee/
bert-base-uncased-finetuned-filtered-0609

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

bert-base-uncased-finetuned-filtered-0609

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1749
Accuracy: 0.9789
Precision: 0.9790
Recall: 0.9789
F1: 0.9789

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.1671	1.0	3180	0.1735	0.9632	0.9648	0.9632	0.9635
0.1384	2.0	6360	0.1120	0.9736	0.9738	0.9736	0.9736
0.1064	3.0	9540	0.1880	0.9635	0.9647	0.9635	0.9635
0.0823	4.0	12720	0.1495	0.9758	0.9759	0.9758	0.9757
0.0426	5.0	15900	0.1766	0.9742	0.9746	0.9742	0.9743
0.0254	6.0	19080	0.1724	0.9777	0.9778	0.9777	0.9777
0.0257	7.0	22260	0.1760	0.9764	0.9767	0.9764	0.9764
0.0017	8.0	25440	0.1672	0.9786	0.9787	0.9786	0.9786
0.0077	9.0	28620	0.1894	0.9789	0.9791	0.9789	0.9789
0.0014	10.0	31800	0.1749	0.9789	0.9790	0.9789	0.9789

Framework versions

Transformers 4.19.2
Pytorch 1.9.1+cu111
Datasets 1.16.1
Tokenizers 0.12.1