---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: indobert_emotion_analysis
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# indobert_emotion_analysis

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9241
- Accuracy: 0.7350
- F1: 0.7350

## 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: 5e-05
- train_batch_size: 40
- eval_batch_size: 40
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7852        | 1.0   | 1343 | 0.7449          | 0.6951   | 0.6951 |
| 0.6399        | 2.0   | 2686 | 0.6838          | 0.7237   | 0.7237 |
| 0.4735        | 3.0   | 4029 | 0.7123          | 0.7293   | 0.7293 |
| 0.3266        | 4.0   | 5372 | 0.8186          | 0.7356   | 0.7356 |
| 0.2114        | 5.0   | 6715 | 0.9241          | 0.7350   | 0.7350 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1