---
base_model: klue/roberta-small
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 [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0128
- Precision: 0.9866
- Recall: 1.0
- F1: 0.9932
- Accuracy: 0.9995

## 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   | 15   | 0.1702          | 0.0767    | 0.1905 | 0.1094 | 0.9585   |
| No log        | 2.0   | 30   | 0.0861          | 0.4163    | 0.5748 | 0.4829 | 0.9793   |
| No log        | 3.0   | 45   | 0.0443          | 0.7741    | 0.8741 | 0.8211 | 0.9919   |
| No log        | 4.0   | 60   | 0.0262          | 0.8984    | 0.9626 | 0.9294 | 0.9970   |
| No log        | 5.0   | 75   | 0.0176          | 0.9734    | 0.9966 | 0.9849 | 0.9994   |
| No log        | 6.0   | 90   | 0.0147          | 0.9767    | 0.9966 | 0.9865 | 0.9994   |
| No log        | 7.0   | 105  | 0.0132          | 0.9866    | 1.0    | 0.9932 | 0.9995   |
| No log        | 8.0   | 120  | 0.0128          | 0.9866    | 1.0    | 0.9932 | 0.9995   |


### Framework versions

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