---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-base-multilingual-cased-reddit-indonesia-sarcastic
  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. -->

# bert-base-multilingual-cased-reddit-indonesia-sarcastic

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4558
- Accuracy: 0.7829
- F1: 0.5338
- Precision: 0.5764
- Recall: 0.4972

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4935        | 1.0   | 309  | 0.4739          | 0.7711   | 0.5186 | 0.5472    | 0.4929 |
| 0.4203        | 2.0   | 618  | 0.4527          | 0.7895   | 0.5547 | 0.5892    | 0.5241 |
| 0.3469        | 3.0   | 927  | 0.5105          | 0.7923   | 0.4957 | 0.6316    | 0.4079 |
| 0.2754        | 4.0   | 1236 | 0.5126          | 0.7746   | 0.5254 | 0.5552    | 0.4986 |
| 0.2208        | 5.0   | 1545 | 0.6012          | 0.7803   | 0.5064 | 0.5782    | 0.4504 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0