--- base_model: klue/roberta-large tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: pogny-128-0.00002 results: [] --- # pogny-128-0.00002 This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.6069 - Accuracy: 0.7691 - F1: 0.7661 ## 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: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.0495 | 1.0 | 603 | 1.3655 | 0.7640 | 0.7622 | | 0.0374 | 2.0 | 1206 | 1.4916 | 0.7674 | 0.7653 | | 0.0222 | 3.0 | 1809 | 1.6069 | 0.7691 | 0.7661 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0a0+b5021ba - Datasets 2.6.2 - Tokenizers 0.14.1