--- library_name: transformers license: mit base_model: roberta-large tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: Modesty_binary results: [] --- # Modesty_binary This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6643 - Accuracy: 0.6782 - Precision: 0.6621 - Recall: 0.7228 - F1: 0.6911 - Auc: 0.6783 ## 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: 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| | No log | 1.0 | 134 | 0.6134 | 0.6558 | 0.6998 | 0.5412 | 0.6103 | 0.6554 | | No log | 2.0 | 268 | 0.6132 | 0.6791 | 0.7149 | 0.5918 | 0.6475 | 0.6788 | | No log | 3.0 | 402 | 0.6643 | 0.6782 | 0.6621 | 0.7228 | 0.6911 | 0.6783 | ### Framework versions - Transformers 4.44.1 - Pytorch 1.11.0 - Datasets 2.12.0 - Tokenizers 0.19.1