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# kcbert-large-finetuned-nsmc

This model is a fine-tuned version of [beomi/kcbert-large](https://huggingface.co/beomi/kcbert-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2576
- Accuracy: 0.9137
- F1: 0.9137

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.267         | 1.0   | 3750 | 0.2231          | 0.9106   | 0.9106 |
| 0.1427        | 2.0   | 7500 | 0.2576          | 0.9137   | 0.9137 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "beomi/kcbert-large", "model-index": [{"name": "kcbert-large-finetuned-nsmc", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:beomi/kcbert-large autotrain_compatible endpoints_compatible region:us