bert-uncased-finetuned-mrpc

alup/bert-uncased-finetuned-mrpc

bert-uncased-finetuned-mrpc is a text classification model from alup. 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. --

Downloads · 30 days

9% of all-time downloads

All-time downloads

Public

Repo size

1.8 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin438 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: May 13, 2023
Updated: May 13, 2023
SHA: 2cbcb689

Try a prompt

Datasets

glue

Model card

From the Hugging Face model README

bert-uncased-finetuned-mrpc

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

Loss: 0.6265
Accuracy: 0.8676
F1: 0.9094

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: 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
No log	1.0	230	0.3924	0.8554	0.9015
No log	2.0	460	0.3575	0.875	0.9128
0.3857	3.0	690	0.6265	0.8676	0.9094

Framework versions

Transformers 4.29.1
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: May 13, 2023
Updated: May 13, 2023