--- base_model: klue/roberta-large tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: pogny-64-0.005 results: [] --- # pogny-64-0.005 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: 1.6848 - Accuracy: 0.4376 - F1: 0.2665 ## 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: 0.005 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 1.9411 | 1.0 | 1205 | 2.0029 | 0.0643 | 0.0078 | | 1.8423 | 2.0 | 2410 | 1.7954 | 0.2545 | 0.1032 | | 1.7098 | 3.0 | 3615 | 1.6848 | 0.4376 | 0.2665 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0a0+b5021ba - Datasets 2.6.2 - Tokenizers 0.14.1