Downloads · 30 days
12
1% of all-time downloads
tteofili/gminus
gminus is a machine learning model from tteofili. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This model is a facebook/bart-large fine-tuned on toxic comments from jigsawtoxicitypred dataset.
Downloads · 30 days
12
1% of all-time downloads
All-time downloads
1.2K
Public
Parameters
406M
3.3 GB on disk
Likes
0
Public
Click a slice to open those files.
.bin1.6 GB · 50%
From the Hugging Face model README
gminusThis model is a facebook/bart-large fine-tuned on toxic comments from jigsaw_toxicity_pred dataset.
This model is not intended to be used for plain inference as it is very likely to predict toxic content.
It is intended to be used instead as "utility model" for detecting and fixing toxic content as its token probability distributions will likely differ from comparable models not trained/fine-tuned over toxic data.
Its name gminus refers to the G- model in Detoxifying Text with MARCO: Controllable Revision with Experts and Anti-Experts.
This model is fine-tuned over toxic comments from jigsaw_toxicity_pred and it is very likely to produce toxic content.
For this reason this model should only be used in combination with other models for the sake of detecting / fixing toxic content, see for example Detoxifying Text with MARCO: Controllable Revision with Experts and Anti-Experts.
This section describes the evaluation protocols and provides the results.
This model was tested on jigsaw_toxic_pred testset.
Model was evaluated using perplexity (on the MLM task).
Perplexity: 1.03
<!-- #### Summary ## Model Examination [optional] - Relevant interpretability work for the model goes here [More Information Needed] ## Environmental Impact Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] - If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] If relevant, include terms and calculations in this section that can help readers understand the model or model card. [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]