squeezebert-mnli-headless-finetuned-mrpc

VitaliiVrublevskyi/squeezebert-mnli-headless-finetuned-mrpc

squeezebert-mnli-headless-finetuned-mrpc is a text classification model from VitaliiVrublevskyi. Use it when you need a label for a piece of text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
Model type: squeezebert
Access: Public
Created: Sep 24, 2023
Updated: Sep 24, 2023
SHA: 2b75fb91

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Datasets

glue

Model card

From the Hugging Face model README

squeezebert-mnli-headless-finetuned-mrpc

This model is a fine-tuned version of squeezebert/squeezebert-mnli-headless on the glue dataset. It achieves the following results on the evaluation set:

Loss: 0.3142
Accuracy: 0.8824
F1: 0.9137

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: 32
eval_batch_size: 32
seed: 73
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	Accuracy	F1
No log	1.0	115	0.4461	0.8162	0.8705
No log	2.0	230	0.3844	0.8407	0.8866
No log	3.0	345	0.3181	0.8848	0.9156
No log	4.0	460	0.3159	0.8775	0.9091
0.3723	5.0	575	0.3142	0.8824	0.9137

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: squeezebert
Created: Sep 24, 2023
Updated: Sep 24, 2023