README.md

metadata

base_model: monologg/koelectra-small-v3-discriminator
tags:
  - generated_from_trainer
datasets:
  - generator
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: chkpt
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: generator
          type: generator
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8826086956521739
          - name: F1
            type: f1
            value: 0.8275730495029622
          - name: Precision
            type: precision
            value: 0.7789981096408317
          - name: Recall
            type: recall
            value: 0.8826086956521739

chkpt

This model is a fine-tuned version of monologg/koelectra-small-v3-discriminator on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 1.2815
• Accuracy: 0.8826
• F1: 0.8276
• Precision: 0.7790
• Recall: 0.8826

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: 32
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	29	1.2815	0.8826	0.8276	0.7790	0.8826

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.1
• Datasets 2.15.0
• Tokenizers 0.15.0