---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: indobert_emotion_base_id
  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. -->

# indobert_emotion_base_id

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: 0.9735
- Accuracy: 0.7535
- F1: 0.7590
- Recall: 0.7578
- Precision: 0.7608

## 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: 32
- eval_batch_size: 32
- 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.4174        | 1.0   | 177  | 0.9081          | 0.7345   | 0.7402 | 0.7565 | 0.7312    |
| 0.3977        | 2.0   | 354  | 0.8161          | 0.7627   | 0.7690 | 0.7746 | 0.7654    |
| 0.2415        | 3.0   | 531  | 0.9306          | 0.7436   | 0.7509 | 0.7565 | 0.7481    |
| 0.1424        | 4.0   | 708  | 0.9735          | 0.7535   | 0.7590 | 0.7578 | 0.7608    |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1