bert-base-uncased-mrpc

JeremiahZ/bert-base-uncased-mrpc

bert-base-uncased-mrpc is a text classification model from JeremiahZ. 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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glue

Model card

From the Hugging Face model README

bert-base-uncased-mrpc

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

Loss: 0.5572
Accuracy: 0.8578
F1: 0.9024
Combined Score: 0.8801

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
No log	1.0	230	0.4111	0.8088	0.8704	0.8396
No log	2.0	460	0.3762	0.8480	0.8942	0.8711
0.4287	3.0	690	0.5572	0.8578	0.9024	0.8801
0.4287	4.0	920	0.6087	0.8554	0.8977	0.8766
0.1172	5.0	1150	0.6524	0.8456	0.8901	0.8678

Framework versions

Transformers 4.20.0.dev0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Languages: en
Created: Jun 21, 2022
Updated: Nov 22, 2024