olm-bert-tiny-december-2022-target-glue-mrpc

muhtasham/olm-bert-tiny-december-2022-target-glue-mrpc

olm-bert-tiny-december-2022-target-glue-mrpc is a text classification model from muhtasham. 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: Feb 1, 2023
Updated: Feb 1, 2023
SHA: f12fe8ef

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Model card

From the Hugging Face model README

olm-bert-tiny-december-2022-target-glue-mrpc

This model is a fine-tuned version of muhtasham/olm-bert-tiny-december-2022 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9243
Accuracy: 0.6299
F1: 0.7146

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6093	4.35	500	0.5848	0.7034	0.7980
0.5487	8.7	1000	0.5863	0.7206	0.8087
0.4724	13.04	1500	0.6881	0.6544	0.7294
0.3752	17.39	2000	0.7549	0.6520	0.7331
0.276	21.74	2500	0.9243	0.6299	0.7146

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.9.1.dev0
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 1, 2023
Updated: Feb 1, 2023