---
language:
- en
metrics:
- accuracy
- f1
- recall
- precision
library_name: transformers
pipeline_tag: text-classification
datasets:
- go_emotions
- ongknsro/ACARIS-v1
---
# Model Card for ACARISBERT-DistilBERT

A 3-class DistilBERT model finetuned on 300k rows of labeled Discord messages, Twitter posts, and Reddit comments (refs soon).
Classes: `["pos", "neg", "neu"]`.



## Model Details

### Model Description

An encoder-only sentiment analysis model finetuned to classify text sequences into three sentiment classes: "pos", "neg", and "neu".



- **Developed by:** OngakkenAI
- **Model type:** DistilBertForSequenceClassification (modified for multiclass)
- **Language(s) (NLP):** en
- **License:** Proprietary (while running eval and testing)
- **Finetuned from model:** DistilBERT

## Uses

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### Direct Use

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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## How to Get Started with the Model

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## Training Details

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### Training Procedure 

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#### Training Hyperparameters

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## Evaluation

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### Results

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#### Summary



## Model Examination [optional]

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### Model Architecture and Objective

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