Text Classification
Transformers
PyTorch
Korean
korean
sentiment-analysis
movie-reviews
koelectra
ordinal-classification
Instructions to use cringepnh/korean-movie-review-predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cringepnh/korean-movie-review-predictor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cringepnh/korean-movie-review-predictor")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cringepnh/korean-movie-review-predictor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "approach": "ordinal", | |
| "model_name": "monologg/koelectra-base-v3-discriminator", | |
| "best_val_mae": 1.288840262582057, | |
| "epochs_run": 5, | |
| "batch_size": 16, | |
| "learning_rate": 2e-05, | |
| "quick_mode": false, | |
| "history": [ | |
| { | |
| "epoch": 1, | |
| "global_step": 9598, | |
| "train_loss": 1.7126157148423014, | |
| "val_loss": 1.6003689557745566, | |
| "val_mae": 1.4430551213921017 | |
| }, | |
| { | |
| "epoch": 2, | |
| "global_step": 19196, | |
| "train_loss": 1.5402111636647995, | |
| "val_loss": 1.5549361996443505, | |
| "val_mae": 1.288840262582057 | |
| }, | |
| { | |
| "epoch": 3, | |
| "global_step": 28794, | |
| "train_loss": 1.4406369831311758, | |
| "val_loss": 1.6341734638037229, | |
| "val_mae": 1.311816192560175 | |
| }, | |
| { | |
| "epoch": 4, | |
| "global_step": 38392, | |
| "train_loss": 1.4285926389105525, | |
| "val_loss": 1.6372355149663511, | |
| "val_mae": 1.2985828904866104 | |
| }, | |
| { | |
| "epoch": 5, | |
| "global_step": 47990, | |
| "train_loss": 1.4052607882171602, | |
| "val_loss": 1.666345580389093, | |
| "val_mae": 1.3000416796915704 | |
| } | |
| ] | |
| } |