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---
license: mit
base_model: indobenchmark/indobert-large-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-large-p1-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. -->
# indobert-large-p1-reddit-indonesia-sarcastic
This model is a fine-tuned version of [indobenchmark/indobert-large-p1](https://huggingface.co/indobenchmark/indobert-large-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4486
- Accuracy: 0.7911
- F1: 0.6184
- Precision: 0.5690
- Recall: 0.6771
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4573 | 1.0 | 309 | 0.4251 | 0.7966 | 0.5684 | 0.6058 | 0.5354 |
| 0.3274 | 2.0 | 618 | 0.4458 | 0.7824 | 0.5955 | 0.5567 | 0.6402 |
| 0.1999 | 3.0 | 927 | 0.5890 | 0.8065 | 0.5412 | 0.6653 | 0.4561 |
| 0.0864 | 4.0 | 1236 | 0.8080 | 0.8023 | 0.5536 | 0.6360 | 0.4901 |
| 0.0391 | 5.0 | 1545 | 1.1299 | 0.7895 | 0.5293 | 0.6007 | 0.4731 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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