---
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: undersampled-review-clf
  results: []
datasets:
- justina/yelp_boba_reviews
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# undersampled-review-clf

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on 
[justina/yelp-boba-reviews](https://huggingface.co/datasets/justina/yelp_boba_reviews) dataset. Undersampling techniques were used to optimize the model for predicting 
Yelp review ratings.

It achieves the following results on the evaluation set:
- Loss: 0.4412
- F1 Macro: 0.7799
- Aucpr Macro: 0.8286
- Accuracy: 0.8464

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Aucpr Macro | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|
| 0.9348        | 1.22  | 100  | 0.7286          | 0.6132   | 0.6244      | 0.6962   |
| 0.7438        | 2.44  | 200  | 0.7857          | 0.6232   | 0.6215      | 0.6735   |
| 0.6275        | 3.66  | 300  | 0.8317          | 0.5976   | 0.6092      | 0.6778   |
| 0.5561        | 4.88  | 400  | 0.8176          | 0.6200   | 0.6238      | 0.6868   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3