CodeNetClassifier – AI Model by petersa2 | AlphaNeural AI | AlphaNeural AI

You can deploy this model and start earning money today!

petersa2/
CodeNetClassifier

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

CodeNetClassifier

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7251
Accuracy: 0.5581

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
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	106	0.7429	0.6078
No log	2.0	212	0.6718	0.6078
No log	3.0	318	0.6943	0.6078
No log	4.0	424	0.7566	0.5940
0.6377	5.0	530	0.7145	0.5596
0.6377	6.0	636	0.7177	0.5952
0.6377	7.0	742	0.6939	0.5458
0.6377	8.0	848	0.7903	0.4716
0.6377	9.0	954	0.7567	0.4727
0.5954	10.0	1060	0.7251	0.5581

Framework versions

Transformers 4.11.3
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.10.3