--- base_model: klue/roberta-large tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: pogny_5_32_0.01 results: [] --- [Visualize in Weights & Biases](https://wandb.ai/bella05/huggingface/runs/x4x55q6l) # pogny_5_32_0.01 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: 1.6853 - 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: 0.01 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| | 2.6592 | 1.0 | 2409 | 2.5341 | 0.4376 | 0.2665 | | 2.4487 | 2.0 | 4818 | 2.4248 | 0.2545 | 0.1032 | | 2.1776 | 3.0 | 7227 | 2.0611 | 0.4376 | 0.2665 | | 1.9033 | 4.0 | 9636 | 2.0099 | 0.4376 | 0.2665 | | 1.7068 | 5.0 | 12045 | 1.6853 | 0.4376 | 0.2665 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.2.2 - Datasets 2.19.1 - Tokenizers 0.19.1