transformers safetensors bert text-classification generated_from_trainer base_model:bert-base-multilingual-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
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-twitter-indonesia-sarcastic
  results: []
---

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# bert-base-multilingual-cased-twitter-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: 0.4720
- Accuracy: 0.8290
- F1: 0.6462
- Precision: 0.6667
- Recall: 0.6269

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5333        | 1.0   | 59   | 0.4792          | 0.75     | 0.0    | 0.0       | 0.0    |
| 0.4642        | 2.0   | 118  | 0.4418          | 0.7910   | 0.3    | 0.9231    | 0.1791 |
| 0.3961        | 3.0   | 177  | 0.4319          | 0.8134   | 0.5192 | 0.7297    | 0.4030 |
| 0.325         | 4.0   | 236  | 0.5264          | 0.7463   | 0.6180 | 0.4955    | 0.8209 |
| 0.2432        | 5.0   | 295  | 0.4624          | 0.8246   | 0.6299 | 0.6667    | 0.5970 |
| 0.1819        | 6.0   | 354  | 0.4261          | 0.8731   | 0.7069 | 0.8367    | 0.6119 |
| 0.148         | 7.0   | 413  | 0.5371          | 0.8545   | 0.6777 | 0.7593    | 0.6119 |
| 0.0995        | 8.0   | 472  | 0.6810          | 0.8396   | 0.6767 | 0.6818    | 0.6716 |
| 0.0843        | 9.0   | 531  | 0.8350          | 0.8209   | 0.5385 | 0.7568    | 0.4179 |


### Framework versions

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