bert-base-uncased-finetuned-hateful-meme

tommilyjones/bert-base-uncased-finetuned-hateful-meme

bert-base-uncased-finetuned-hateful-meme is a text classification model from tommilyjones. 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: Aug 5, 2023
Updated: Aug 5, 2023
SHA: 17e97c39

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Base models

Model card

From the Hugging Face model README

bert-base-uncased-finetuned-hateful-meme

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

Loss: 2.0538
Accuracy: 0.544

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5795	1.0	532	0.7869	0.564
0.5101	2.0	1064	0.8646	0.56
0.4455	3.0	1596	0.9011	0.538
0.3926	4.0	2128	1.1856	0.542
0.3387	5.0	2660	1.1351	0.552
0.3056	6.0	3192	1.3704	0.55
0.2942	7.0	3724	1.7288	0.538
0.2665	8.0	4256	1.7215	0.544
0.2498	9.0	4788	1.8634	0.542
0.2357	10.0	5320	2.0538	0.544

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.14.3
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Aug 5, 2023
Updated: Aug 5, 2023