---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: klue-roberta-large-klue-2016klp-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# klue-roberta-large-klue-2016klp-ner

This model is a fine-tuned version of [soddokayo/klue-roberta-large-klue-ner](https://huggingface.co/soddokayo/klue-roberta-large-klue-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0947
- Precision: 0.7693
- Recall: 0.8093
- F1: 0.7888
- Accuracy: 0.9756

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 366  | 0.0970          | 0.7       | 0.784  | 0.7396 | 0.9685   |
| 0.0982        | 2.0   | 732  | 0.0853          | 0.7982    | 0.8173 | 0.8076 | 0.9770   |
| 0.035         | 3.0   | 1098 | 0.0947          | 0.7693    | 0.8093 | 0.7888 | 0.9756   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.11.0