soft-search

evamaxfield/soft-search

soft-search is a text classification model from evamaxfield. 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: distilbert
Access: Public
Created: Aug 4, 2022
Updated: Dec 23, 2023
SHA: 19a7f154

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Base models

Model card

From the Hugging Face model README

soft-search

This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5558
F1: 0.5960
Accuracy: 0.7109
Precision: 0.5769
Recall: 0.6164

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: 3e-05
train_batch_size: 12
eval_batch_size: 12
seed: 42
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	F1	Accuracy	Precision	Recall
0.5939	1.0	71	0.5989	0.0533	0.6635	1.0	0.0274
0.5903	2.0	142	0.5558	0.5960	0.7109	0.5769	0.6164
0.4613	3.0	213	0.6670	0.5641	0.6777	0.5301	0.6027
0.4454	4.0	284	0.7647	0.5541	0.6872	0.5467	0.5616
0.2931	5.0	355	0.8726	0.5139	0.6682	0.5211	0.5068

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Aug 4, 2022
Updated: Dec 23, 2023