distilbert-base-uncased-finetuned-stsb

trinadutta/distilbert-base-uncased-finetuned-stsb

distilbert-base-uncased-finetuned-stsb is a text classification model from trinadutta. 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: May 18, 2023
Updated: May 18, 2023
SHA: 9f29984d

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Datasets

glue

Model card

From the Hugging Face model README

distilbert-base-uncased-finetuned-stsb

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

Loss: 0.5388
Pearson: 0.8740
Spearmanr: 0.8704

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: 16
eval_batch_size: 16
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	Pearson	Spearmanr
No log	1.0	360	0.6683	0.8599	0.8575
1.0348	2.0	720	0.5413	0.8715	0.8685
0.3974	3.0	1080	0.5560	0.8725	0.8692
0.3974	4.0	1440	0.5666	0.8737	0.8703
0.2516	5.0	1800	0.5388	0.8740	0.8704

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu117
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: May 18, 2023
Updated: May 18, 2023