---
library_name: transformers
base_model: skt/kobert-base-v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: kobert-sentiment-3class-restaurant-fintuned
  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. -->

# kobert-sentiment-3class-restaurant-fintuned

This model is a fine-tuned version of [skt/kobert-base-v1](https://huggingface.co/skt/kobert-base-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5201
- Accuracy: 0.7820
- F1 Macro: 0.7577

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
| 0.5298        | 1.0   | 7020  | 0.5178          | 0.7721   | 0.7467   |
| 0.4725        | 2.0   | 14040 | 0.5096          | 0.7817   | 0.7557   |
| 0.3954        | 3.0   | 21060 | 0.5201          | 0.7820   | 0.7577   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1