---
base_model: vitus9988/klue-roberta-small-ner-identified
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: klue-roberta-small-ner-identified
  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. -->

# klue-roberta-small-ner-identified

This model is a fine-tuned version of [vitus9988/klue-roberta-small-ner-identified](https://huggingface.co/vitus9988/klue-roberta-small-ner-identified) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1304
- Precision: 0.9222
- Recall: 0.9520
- F1: 0.9369
- Accuracy: 0.9790

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 4    | 0.8023          | 0.1377    | 0.1231 | 0.1300 | 0.9178   |
| No log        | 2.0   | 8    | 0.4197          | 0.5419    | 0.5580 | 0.5498 | 0.9431   |
| No log        | 3.0   | 12   | 0.2760          | 0.6764    | 0.7146 | 0.6950 | 0.9564   |
| No log        | 4.0   | 16   | 0.2062          | 0.7835    | 0.8544 | 0.8174 | 0.9617   |
| No log        | 5.0   | 20   | 0.1685          | 0.8299    | 0.8946 | 0.8610 | 0.9711   |
| No log        | 6.0   | 24   | 0.1470          | 0.8854    | 0.9295 | 0.9069 | 0.9758   |
| No log        | 7.0   | 28   | 0.1350          | 0.9138    | 0.9460 | 0.9297 | 0.9778   |
| No log        | 8.0   | 32   | 0.1304          | 0.9222    | 0.9520 | 0.9369 | 0.9790   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1