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---
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
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