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---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-base-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-base-p1-reddit-indonesia-sarcastic
This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9796
- Accuracy: 0.7881
- F1: 0.5335
- Precision: 0.5938
- Recall: 0.4844
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4385 | 1.0 | 309 | 0.4258 | 0.7980 | 0.5675 | 0.6111 | 0.5297 |
| 0.3451 | 2.0 | 618 | 0.4345 | 0.8030 | 0.6283 | 0.5949 | 0.6657 |
| 0.2404 | 3.0 | 927 | 0.5054 | 0.8016 | 0.5318 | 0.6490 | 0.4504 |
| 0.1326 | 4.0 | 1236 | 0.7033 | 0.7860 | 0.5452 | 0.5820 | 0.5127 |
| 0.0787 | 5.0 | 1545 | 0.9796 | 0.7881 | 0.5335 | 0.5938 | 0.4844 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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