bert-finetuned-spam

ana-grassmann/bert-finetuned-spam

bert-finetuned-spam is a machine learning model from ana-grassmann. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.

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

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Hugging Face

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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: May 6, 2024
Updated: May 29, 2024
SHA: d2ab6124

Base models

google-bert/bert-base-uncased

Model card

From the Hugging Face model README

bert-finetuned-spam

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

Loss: 0.1942
Accuracy: 0.952
F1: 0.9502
Precision: 0.9871
Recall: 0.916

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: 2.5719605731158755e-06
train_batch_size: 4
eval_batch_size: 2
seed: 19
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.2449	1.0	2250	0.2435	0.901	0.8930	0.9718	0.826
0.2545	2.0	4500	0.2138	0.937	0.9336	0.9866	0.886
0.1397	3.0	6750	0.2162	0.944	0.9413	0.9890	0.898
0.1184	4.0	9000	0.2134	0.946	0.9436	0.9869	0.904
0.2056	5.0	11250	0.1942	0.952	0.9502	0.9871	0.916

Framework versions

PEFT 0.11.1
Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Library: peft
License: apache-2.0
Created: May 6, 2024
Updated: May 29, 2024