---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: XLM-RoBERTa-Base-Sundanese-Emotion-Classifier-v20241222170134
  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. -->

# XLM-RoBERTa-Base-Sundanese-Emotion-Classifier-v20241222170134

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0177
- Accuracy: 1.0
- F1 Micro: 1.0
- F1 Macro: 1.0
- F1 Weighted: 1.0

## 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: 64
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Micro | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:-----------:|
| 1.0664        | 2.5   | 100  | 0.4432          | 0.9167   | 0.9167   | 0.9143   | 0.9143      |
| 0.4356        | 5.0   | 200  | 0.1068          | 0.9167   | 0.9167   | 0.9143   | 0.9143      |
| 0.19          | 7.5   | 300  | 0.0109          | 1.0      | 1.0      | 1.0      | 1.0         |
| 0.1069        | 10.0  | 400  | 0.0090          | 1.0      | 1.0      | 1.0      | 1.0         |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0