--- base_model: klue/roberta-large tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: pogny-64-0.000001 results: [] --- # pogny-64-0.000001 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: 1.2381 - Accuracy: 0.7685 - F1: 0.7667 ## 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: 1e-06 - train_batch_size: 64 - eval_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.0912 | 1.0 | 1205 | 1.2147 | 0.7687 | 0.7677 | | 0.0828 | 2.0 | 2410 | 1.2212 | 0.7681 | 0.7667 | | 0.0787 | 3.0 | 3615 | 1.2381 | 0.7685 | 0.7667 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0a0+b5021ba - Datasets 2.6.2 - Tokenizers 0.14.1