| --- |
| 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 |
| --- |
| |
| <!-- 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. --> |
|
|
| # chkpt |
|
|
| This model is a fine-tuned version of [monologg/koelectra-small-v3-discriminator](https://huggingface.co/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 |
|
|
