--- library_name: transformers license: apache-2.0 base_model: distilroberta-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: platzi-osvaldo-course-mrpc-glue-osvaldo-trejo results: [] --- # platzi-osvaldo-course-mrpc-glue-osvaldo-trejo This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.0336 - Accuracy: 0.8260 - F1: 0.8774 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| | 0.5207 | 1.0893 | 500 | 0.4251 | 0.8284 | 0.8694 | | 0.3566 | 2.1786 | 1000 | 0.9369 | 0.8211 | 0.8717 | | 0.2331 | 3.2680 | 1500 | 1.0557 | 0.8309 | 0.8848 | | 0.1073 | 4.3573 | 2000 | 1.0336 | 0.8260 | 0.8774 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.20.3