---
base_model: citizenlab/twitter-xlm-roberta-base-sentiment-finetunned
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Malay-Sentiment3
  results: []
---

<!-- 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. -->

# Malay-Sentiment3

This model is a fine-tuned version of [citizenlab/twitter-xlm-roberta-base-sentiment-finetunned](https://huggingface.co/citizenlab/twitter-xlm-roberta-base-sentiment-finetunned) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7976
- Accuracy: 0.7696

## 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: 16
- eval_batch_size: 16
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.713         | 1.0   | 723  | 0.5733          | 0.7633   |
| 0.5687        | 2.0   | 1446 | 0.5964          | 0.7640   |
| 0.3369        | 3.0   | 2169 | 0.6799          | 0.7737   |
| 0.2823        | 4.0   | 2892 | 0.7976          | 0.7696   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cpu
- Datasets 2.14.5
- Tokenizers 0.15.0