
# DistilRoBERTa base fintuned condition classifier

# Table of Contents

1. [Model Details](#model-details)
2. [Training Details](#training-details)
3. [Evaluation](#evaluation)
4. [How To Get Started With the Model](#how-to-get-started-with-the-model)

# Model Details

## Model Description

This model is fine-tuned for a condition classification version of the [DistilRoBERTa-base model](https://huggingface.co/distilroberta-base).
This model is case-sensitive: it makes a difference between english and English.


- **Fine-tuned by:** Ban Ursus
- **Model type:** Transformer-based language model
- **Language(s) (NLP):** English
- **License:** Apache 2.0
- **Related Models:** [DistilRoBERTa-base model](https://huggingface.co/distilroberta-base)
- **Resources for more information:** 
  - [GitHub Repository](https://github.com/BanSangSu/Hugging_Face_NLP_Course/tree/main/Chapter5)
  


# Training Details

This model was fine-tuned 5 epochs using [Drug Review Dataset](https://archive.ics.uci.edu/dataset/462/drug+review+dataset+drugs+com). Therefore, you can improve the accuracy of this model just by training more.


# Evaluation

Validation results:

| Accuracy | F1 score |
|:----:|:----:|
| 0.63 | 0.58 |

Note: Rounded to 2 decimal places


# How to Get Started With the Model

Follow the Section 2 **Try it out!** of the [GitHub Repository](https://github.com/BanSangSu/Hugging_Face_NLP_Course/tree/main/Chapter5).
{"language": "en", "license": "apache-2.0", "tags": ["exbert"], "datasets": ["drug-review"]}
transformers safetensors roberta text-classification exbert en dataset:drug-review license:apache-2.0 autotrain_compatible endpoints_compatible region:us