| base_model: kykim/albert-kor-base | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - nsmc | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: electra2 | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: nsmc | |
| type: nsmc | |
| config: default | |
| split: test | |
| args: default | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.89276 | |
| <!-- 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. --> | |
| # electra2 | |
| This model is a fine-tuned version of [kykim/albert-kor-base](https://huggingface.co/kykim/albert-kor-base) on the nsmc dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3037 | |
| - Accuracy: 0.8928 | |
| ## 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-06 | |
| - 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: cosine | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| | |
| | 0.2815 | 1.0 | 9375 | 0.2801 | 0.8863 | | |
| | 0.2329 | 2.0 | 18750 | 0.2705 | 0.8920 | | |
| | 0.1949 | 3.0 | 28125 | 0.3037 | 0.8928 | | |
| ### Framework versions | |
| - Transformers 4.31.0 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.14.4 | |
| - Tokenizers 0.13.3 | |