kdrt_content / README.md
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---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: kdrt_content
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. -->
# kdrt_content
This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2446
- Accuracy: 0.9231
- Precision: 0.9231
- Recall: 0.9231
- F1: 0.9231
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 59 | 0.4204 | 0.8291 | 0.8291 | 0.8291 | 0.8291 |
| No log | 2.0 | 118 | 0.2446 | 0.9231 | 0.9231 | 0.9231 | 0.9231 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1