distilbert-base-uncased-finetuned-mathQA

rootacess/distilbert-base-uncased-finetuned-mathQA

distilbert-base-uncased-finetuned-mathQA is a text classification model from rootacess. 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: distilbert
Access: Public
Created: Mar 6, 2023
Updated: Mar 23, 2023
SHA: 822ffcd7

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Model card

From the Hugging Face model README

distilbert-base-uncased-finetuned-mathQA

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0752
Accuracy: 0.9857
F1: 0.9857

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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3155	1.0	1865	0.0997	0.9727	0.9727
0.0726	2.0	3730	0.0813	0.9826	0.9825
0.0292	3.0	5595	0.0752	0.9857	0.9857

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Mar 6, 2023
Updated: Mar 23, 2023