
# Indo RoBERTa Emotion Classifier

Indo RoBERTa Emotion Classifier is emotion classifier based on [Indo-roberta](https://huggingface.co/flax-community/indonesian-roberta-base) model. It was trained on the trained on [IndoNLU EmoT](https://huggingface.co/datasets/indonlu) dataset. The model used was [Indo-roberta](https://huggingface.co/flax-community/indonesian-roberta-base) and was transfer-learned to an emotion classifier model. Based from the [IndoNLU bencmark](https://www.indobenchmark.com/), the model achieve an f1-macro of 72.05%, accuracy of 71.81%, precision of 72.47% and recall of 71.94%.

## Model

The model was trained on 7 epochs with learning rate 2e-5. Achieved different metrics as shown below.

| Epoch | Training Loss | Validation Loss | Accuracy | F1       | Precision | Recall   |
|-------|---------------|-----------------|----------|----------|-----------|----------|
|     1 |      1.300700 |        1.005149 | 0.622727 | 0.601846 |  0.640845 | 0.611144 |
|     2 |      0.806300 |        0.841953 | 0.686364 | 0.694096 |  0.701984 | 0.696657 |
|     3 |      0.591900 |        0.796794 | 0.686364 | 0.696573 |  0.707520 | 0.691671 |
|     4 |      0.441200 |        0.782094 | 0.722727 | 0.724359 |  0.725985 | 0.730229 |
|     5 |      0.334700 |        0.809931 | 0.711364 | 0.720550 |  0.718318 | 0.724608 |
|     6 |      0.268400 |        0.812771 | 0.718182 | 0.724192 |  0.721222 | 0.729195 |
|     7 |      0.226000 |        0.828461 | 0.725000 | 0.733625 |  0.731709 | 0.735800 |

## How to Use
### As Text Classifier
```python
from transformers import pipeline
pretrained_name = "StevenLimcorn/indonesian-roberta-base-emotion-classifier"
nlp = pipeline(
    "sentiment-analysis",
    model=pretrained_name,
    tokenizer=pretrained_name
)
nlp("Hal-hal baik akan datang.")
```
## Disclaimer
Do consider the biases which come from both the pre-trained RoBERTa model and the `EmoT` dataset that may be carried over into the results of this model.
## Author
Indonesian RoBERTa Base Emotion Classifier was trained and evaluated by [Steven Limcorn](https://github.com/stevenlimcorn). All computation and development are done on Google Colaboratory using their free GPU access.

If used, please cite
```bibtex
@misc {steven_limcorn_2023,
	author       = { {Steven Limcorn} },
	title        = { indonesian-roberta-base-emotion-classifier (Revision e8a9cb9) },
	year         = 2023,
	url          = { https://huggingface.co/StevenLimcorn/indonesian-roberta-base-emotion-classifier },
	doi          = { 10.57967/hf/0681 },
	publisher    = { Hugging Face }
}
```
{"language": "id", "license": "mit", "tags": ["roberta"], "datasets": ["indonlu"], "widget": [{"text": "Hal-hal baik akan datang."}]}
transformers pytorch tf safetensors roberta text-classification id dataset:indonlu doi:10.57967/hf/0681 license:mit autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #safetensors #roberta #text-classification #id #dataset-indonlu #doi-10.57967/hf/0681 #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 

Indo RoBERTa Emotion Classifier
===============================


Indo RoBERTa Emotion Classifier is emotion classifier based on Indo-roberta model. It was trained on the trained on IndoNLU EmoT dataset. The model used was Indo-roberta and was transfer-learned to an emotion classifier model. Based from the IndoNLU bencmark, the model achieve an f1-macro of 72.05%, accuracy of 71.81%, precision of 72.47% and recall of 71.94%.


Model
-----


The model was trained on 7 epochs with learning rate 2e-5. Achieved different metrics as shown below.



How to Use
----------


### As Text Classifier


Disclaimer
----------


Do consider the biases which come from both the pre-trained RoBERTa model and the 'EmoT' dataset that may be carried over into the results of this model.


Author
------


Indonesian RoBERTa Base Emotion Classifier was trained and evaluated by Steven Limcorn. All computation and development are done on Google Colaboratory using their free GPU access.


If used, please cite



### As Text Classifier


Disclaimer
----------


Do consider the biases which come from both the pre-trained RoBERTa model and the 'EmoT' dataset that may be carried over into the results of this model.


Author
------


Indonesian RoBERTa Base Emotion Classifier was trained and evaluated by Steven Limcorn. All computation and development are done on Google Colaboratory using their free GPU access.


If used, please cite
TAGS
#transformers #pytorch #tf #safetensors #roberta #text-classification #id #dataset-indonlu #doi-10.57967/hf/0681 #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### As Text Classifier


Disclaimer
----------


Do consider the biases which come from both the pre-trained RoBERTa model and the 'EmoT' dataset that may be carried over into the results of this model.


Author
------


Indonesian RoBERTa Base Emotion Classifier was trained and evaluated by Steven Limcorn. All computation and development are done on Google Colaboratory using their free GPU access.


If used, please cite
passage: TAGS
#transformers #pytorch #tf #safetensors #roberta #text-classification #id #dataset-indonlu #doi-10.57967/hf/0681 #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 
### As Text Classifier


Disclaimer
----------


Do consider the biases which come from both the pre-trained RoBERTa model and the 'EmoT' dataset that may be carried over into the results of this model.


Author
------


Indonesian RoBERTa Base Emotion Classifier was trained and evaluated by Steven Limcorn. All computation and development are done on Google Colaboratory using their free GPU access.


If used, please cite