finetuned-bert-mrpc

shahma/finetuned-bert-mrpc

finetuned-bert-mrpc is a text classification model from shahma. 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: bert
Access: Public
Created: Jun 30, 2022
Updated: Jun 30, 2022
SHA: 653009a0

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Datasets

glue

Model card

From the Hugging Face model README

finetuned-bert-mrpc

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

Loss: 0.4266
Accuracy: 0.8603
F1: 0.9032

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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5475	1.0	230	0.4024	0.8211	0.8785
0.3309	2.0	460	0.3702	0.8529	0.8986
0.1716	3.0	690	0.4266	0.8603	0.9032

Framework versions

Transformers 4.20.1
Pytorch 1.12.0+cu102
Datasets 2.3.2
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jun 30, 2022
Updated: Jun 30, 2022