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token_classification

Token Classification
Transformers
PyTorch
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Safetensors
bert
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token_classification
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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- klue
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: token_classification
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: klue
      type: klue
      config: ner
      split: validation
      args: ner
    metrics:
    - name: Precision
      type: precision
      value: 0.5834885164494104
    - name: Recall
      type: recall
      value: 0.6555090655509066
    - name: F1
      type: f1
      value: 0.6174055829228243
    - name: Accuracy
      type: accuracy
      value: 0.9235426702611924
---

<!-- 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. -->

# token_classification

This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2397
- Precision: 0.5835
- Recall: 0.6555
- F1: 0.6174
- Accuracy: 0.9235

## 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: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 313  | 0.2569          | 0.5378    | 0.6297 | 0.5801 | 0.9190   |
| 0.3194        | 2.0   | 626  | 0.2397          | 0.5835    | 0.6555 | 0.6174 | 0.9235   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3