---
license: apache-2.0
base_model: Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: indonesian-distilbert-base-cased-finetuned-indonlu
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: indonlu
      type: indonlu
      config: emot
      split: validation
      args: emot
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6113636363636363
    - name: Precision
      type: precision
      value: 0.6057688190944959
    - name: Recall
      type: recall
      value: 0.6113636363636363
    - name: F1
      type: f1
      value: 0.6068671444135532
---

<!-- 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. -->

# indonesian-distilbert-base-cased-finetuned-indonlu

This model is a fine-tuned version of [Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion](https://huggingface.co/Toshifumi/distilbert-base-multilingual-cased-finetuned-emotion) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1300
- Accuracy: 0.6114
- Precision: 0.6058
- Recall: 0.6114
- F1: 0.6069

## 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: 1e-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
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 221  | 1.2623          | 0.475    | 0.4817    | 0.475  | 0.4458 |
| No log        | 2.0   | 442  | 1.0937          | 0.55     | 0.5555    | 0.55   | 0.5444 |
| 1.2289        | 3.0   | 663  | 1.0749          | 0.5886   | 0.6003    | 0.5886 | 0.5898 |
| 1.2289        | 4.0   | 884  | 1.0836          | 0.5818   | 0.6019    | 0.5818 | 0.5800 |
| 0.7857        | 5.0   | 1105 | 1.1300          | 0.6114   | 0.6058    | 0.6114 | 0.6069 |
| 0.7857        | 6.0   | 1326 | 1.1595          | 0.6      | 0.5996    | 0.6    | 0.5984 |
| 0.5288        | 7.0   | 1547 | 1.1767          | 0.6      | 0.5986    | 0.6    | 0.5958 |
| 0.5288        | 8.0   | 1768 | 1.2195          | 0.6      | 0.5969    | 0.6    | 0.5952 |
| 0.5288        | 9.0   | 1989 | 1.2422          | 0.5932   | 0.5915    | 0.5932 | 0.5909 |
| 0.3685        | 10.0  | 2210 | 1.2406          | 0.5841   | 0.5842    | 0.5841 | 0.5830 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2