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---
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
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