---
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: full-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. -->

# full-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.

It achieves the following results on the evaluation set:
- Loss: 0.8198
- F1 Macro: 0.6358
- Aucpr Macro: 0.6658
- Accuracy: 0.7185

## 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: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|
| 0.723         | 0.43  | 500  | 0.7576          | 0.5979   | 0.6652      | 0.6831   |
| 0.7307        | 0.87  | 1000 | 0.6862          | 0.6368   | 0.6752      | 0.7185   |
| 0.5828        | 1.3   | 1500 | 0.7398          | 0.6439   | 0.6661      | 0.7255   |
| 0.6236        | 1.73  | 2000 | 0.7878          | 0.6212   | 0.6690      | 0.7069   |
| 0.3739        | 2.16  | 2500 | 0.8138          | 0.6447   | 0.6752      | 0.7170   |
| 0.4235        | 2.6   | 3000 | 0.8048          | 0.6490   | 0.6673      | 0.7255   |
| 0.3684        | 3.03  | 3500 | 0.9615          | 0.6483   | 0.6715      | 0.7205   |
| 0.3243        | 3.46  | 4000 | 1.0931          | 0.6432   | 0.6632      | 0.7235   |


### Framework versions

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